Rethinking Smart Home Design: Integrating Architectural

Rethinking Smart Home Design: Integrating ArchitecturalPerspectives and Technologically-driven Design Thinking within a

Framework

Archi Dasgupta

Dissertation submitted to the Faculty of the

Virginia Polytechnic Institute and State University

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

in

Computer Science and Applications

Denis Gračanin, Chair

Douglas A. Bowman

R. Benjamin Knapp

James R. Jones

Krešimir Matković

August 9, 2021

Blacksburg, Virginia

Keywords: Smart Built Environment (SBE), Smart Home, Technology, Architecture,

Design, Internet of Things (IoT), Human Computer Interaction (HCI), Human Centered

Design (HCD), Ambient Intelligent Environment, Human Building Interaction (HBI)

Copyright 2021, Archi Dasgupta


FrameworkArchi Dasgupta

(ABSTRACT)

Smart homes, equipped with sensing, actuation, communication, and computation capabili-

ties, enable automation and adaptation according to the occupants’ needs. These capabilities

work together to build holistic spatial and living experiences for the occupants. Smart tech-

nologies significantly impact spatial experiences, making smart home design an architectural

problem along with a technological problem. Nevertheless, smart home research focuses pri-

marily on standalone technological solutions, where the spatial/architectural aspect is largely

absent. We argue that addressing the technological aspects isolated from the spatial context

leads to reduced experiences for the users/occupants, as this practice blocks the pathways

to develop holistic and innovative smart home solutions. Hence, we focus on bridging the

gap between architectural and technological components in smart home research. To this

end, we studied the design of smart homes from related disciplines, i.e., architecture, human-

computer interaction, human–building interaction, industrial manufacturing, and modular

assembly. Our research used the triangulation technique to consult with subject matter ex-

perts (researchers, practitioners, and professors of related disciplines) to understand current

design processes. We conducted ethnographic studies, focus group studies, and in-depth

interviews and identified challenges and best practices for smart home design process. Our

investigation recognizes a nascent research problem where the technological and architec-

tural aspects come together in the design thinking of smart home designers. We expanded

the scope of design thinking to include three primary elements of smart homes- embed-

ded technology, architectural elements, and occupants’ needs. This multidisciplinary and

complex process requires a well-defined design framework to methodically address all the

issues associated with it. Hence, we developed a user-centered design framework, ArTSE,

through an iterative Delphi study to guide the smart home design process. ArTSE stands

for “Architecture and Technology in Smart Home DEsign”. This framework guides user

requirements collection using HCI models, technology decision making, interaction modal-

ities selection, the decision support system for schematic design, technology infrastructure

development, and production of the necessary documentation. This framework is an evolu-

tion of the normative theory in the architectural design process that caters to the needs of

smart home design. For defining implementation strategies, we applied the framework to a

case study– a smart reconfigurable space design project. Overall, we document different as-

pects of the smart home design process and provide a comprehensive guideline for designers,

researchers, and practitioners in this area.


FrameworkArchi Dasgupta

(GENERAL AUDIENCE ABSTRACT)

Smart homes have automation systems so that occupants can monitor and control lighting,

heating, electronic devices, etc. remotely using phones/computers. Smart home devices

and components are equipped with sensing, actuation, communication, and computation

capabilities, to enable automation and adaptation according to the occupants’ needs. These

capabilities work together to build holistic spatial and living experiences for the occupants.

Smart technologies significantly impact spatial experiences, making smart home design an

architectural problem along with a technological problem. Nevertheless, smart home research

focuses primarily on standalone technological solutions, where the spatial/architectural as-

pect is largely absent. We argue that addressing the technological aspects isolated from

the spatial context leads to reduced experiences for the occupants, as this practice blocks

the pathways to develop innovative smart home solutions. Hence, we focus on bridging

the gap between architectural and technological components in smart home research. To

this end, we studied the design of smart homes from related disciplines, i.e., architecture,

human-computer interaction, human–building interaction, industrial manufacturing, and

modular construction. We consulted with subject matter experts (researchers, practitioners,

and professors of related disciplines) to understand current design processes. We conducted

ethnographic studies, focus group studies, and in-depth interviews and identified challenges

and best practices for smart home design process. Our investigation recognizes a nascent

research problem where the technological and architectural aspects come together in the de-

sign thinking of smart home designers. We expanded the scope of design thinking to include

three primary elements of smart homes- embedded technology, architectural elements, and

occupants’ needs. This multidisciplinary and complex process requires a well-defined design

framework to methodically address all the issues associated with it. Hence, we developed a

user-centered design framework, ArTSE, through an iterative procedure to guide the smart

home design process. ArTSE stands for “Architecture and Technology in Smart Home

DEsign”. This framework guides user requirements collection using HCI models, technology

decision making, interaction modalities selection, the decision support system for schematic

design, technology infrastructure development, and production of the necessary documen-

tation. For defining implementation strategies, we applied the framework to a case study–

a smart reconfigurable space design project. Overall, we document different aspects of the

smart home design process and provide a comprehensive guideline for designers, researchers,

and practitioners in this area.

v

Dedication

To my parents (Dasgupta Asim Kumar and Sumana Gupta),

who gave me wings to fly.

To my siblings (Urmee, Shamit), dearest friends, and my advisor, who were the wind

beneath my wings.

vi

Acknowledgments

I am forever grateful to my parents for being my biggest supporters. They inspired me to

live, love, and laugh through even the toughest of times. They gave me the courage to dream

and the confidence to pursue those dreams against all odds. My heartfelt gratitude to my

siblings, my partners in crime, for always lifting me up and giving me strength. This journey

would not have been possible without the support and encouragement of my adoring family.

I would like to thank my advisor, Dr. Denis Gračanin, for believing in me. I took a big

leap of faith by changing the course of my academic path, he was the one who guided me

through the ups and downs with extraordinary patience. My sincerest thanks to my com-

mittee members who have always encouraged me and helped pave the pathway.

It was a joyful ride from the beginning to the end, thanks to my beloved friends. I would like

to acknowledge the constant support from my dearest friends (Sabrina Afrin, Bushra Taw-

fiq Chowdhury, Sajal Dash, Rubayet Elahi, Saili Gadgil, Navyaram Kondur, Mark Manuel,

Rehnuma Nurain Maria, AKM Fazla Mehrab, Divya Nautiyal, Nabil Nowak, Fabiha Now-

shin, Asifur Rahman, Sazzadur Rahaman, Jenat Rahman, Farhanaz Sharmin, Farin Sid-

diquee, Munawwar M. Sohul, Tahmida Akter Swarna, Ipsita Hamid Trisha, and Soumya

Vundekode). A very special shout out to Sabrina Afrin and Sajal Dash for keeping my spir-

its up and motivating me to push through that last mile.

I would also like to convey my sincerest thanks to my collaborators (Shaoli Dasgupta,

Poorvesh Dongre, Mohamed Handosa, Gunnar Nelson, Reza Tasooji, and Sam Williams),

working with whom was a great learning experience.

Funding Acknowledgment: My research was supported by the Housing Virginia Re-

vii

search Grant (January 2017 – May 2018) and funding from Institute for Creativity, Arts,

and Technology (ICAT) for conducting user studies.

Declaration of Collaboration: The research benefited from several collaborators. Reza

Tasooji (Virginia Tech, USA), Mohamed Handosa (Mansoura University, Egypt), Mark

Manuel (Virginia Tech, USA), Matthew LaGro (OSIsoft, USA), and Mike Mihuc (OSIsoft,

USA) contributed to the work included in Chapter 5.

Archi Dasgupta

Blacksburg, Virginia, USA.

Aug 9, 2021.

viii

Contents

List of Figures xiii

1 Introduction 1

1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.3.1 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.3.2 Goals and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.4 Research Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.5 Research Contributions: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.6 Dissertation Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2 Literature Review 15

2.1 Review Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.2 Overview of Smart Home Design and Research . . . . . . . . . . . . . . . . . 18

2.2.1 Goals and Research Focus . . . . . . . . . . . . . . . . . . . . . . . . 18

2.2.2 The Underlying Technology that Enables IoT-based Smart Homes . . 20

2.2.3 The Spatial Elements of Built Environments . . . . . . . . . . . . . . 26

ix

2.2.4 The Architectural Concern for Smart Homes: Contemporary HCI,

HBI, and Architectural Research . . . . . . . . . . . . . . . . . . . . 28

2.3 Guiding Principles and Techniques of Design Processes . . . . . . . . . . . . 31

2.3.1 Existing Design Processes as a Baseline for Smart Home Design Frame-

work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.3.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

2.4 Other Concerns for Smart Home Design . . . . . . . . . . . . . . . . . . . . 42

2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3 Understanding the State of the Art of Smart Home Design Process 46

3.1 Ethnographic Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.2 Focus Group Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

3.3 In-depth Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

4 Iterative Development of a Smart Home Design Framework 73

4.1 Developing First Iteration of the Proposed Framework . . . . . . . . . . . . 77

4.2 Process of Finalizing the Framework . . . . . . . . . . . . . . . . . . . . . . 82

4.3 Final Framework: Architecture and Technology in Smart Home DEsign (ArTSE) 85

4.3.1 Phase 1: Ideation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

4.3.2 Phase 2: General Study . . . . . . . . . . . . . . . . . . . . . . . . . 91

x

4.3.3 Phase 3: Development . . . . . . . . . . . . . . . . . . . . . . . . . . 99

4.3.4 Phase 4: Implementation . . . . . . . . . . . . . . . . . . . . . . . . . 104

4.4 Reaching Consensus Through the Delphi study– . . . . . . . . . . . . . . . . 106

4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

5 Technological Aspects of the ArTSE Framework 110

5.1 A Reference Implementation of Technology Infrastructure [153, 155] . . . . . 111

5.1.1 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

5.1.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

5.1.3 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

5.1.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

5.2 Interaction Design: A Discussion on Four Interaction Modalities [76] . . . . 121

6 Dissemination 126

6.1 Case Study: The SReS Project . . . . . . . . . . . . . . . . . . . . . . . . . 127

6.1.1 Qualitative Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

6.1.2 Quantitative Feedback Using SUS Score . . . . . . . . . . . . . . . . 133

6.1.3 Suggestions From the Case-study Participants Regarding the Framework136

6.2 Dissemination Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

7 Conclusion 138

xi

Bibliography 143

Appendices 163

Appendix A Incremental Development of SBE Design Framework 164

Appendix B User Study: Individual, In-depth Interviews 178

B.1 Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

xii

List of Figures

1.1 Left: Two dimensions of traditional built environment design [48]. Right:

Three dimensions of smart built environment (SBE) design [48]. . . . . . . . 3

1.2 Example of an SBE; Courtesy– Virginia Tech FutureHAUS [48, 161] . . . . . 4

1.3 Research approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.4 Timeline for focus group studies, interviews, and Delphi studies. . . . . . . . 12

2.1 Layers of smart home technology stack. . . . . . . . . . . . . . . . . . . . . . 21

2.2 System architecture example (reproduced from [48, 50]). . . . . . . . . . . . 22

2.3 Different elements of building systems (reproduced from [13]). . . . . . . . . 27

2.4 Steps of the digital design process proposed by Pahl et al., modeled by McMa-

hon et al. (reproduced from [13, 130]). . . . . . . . . . . . . . . . . . . . . . 33

2.5 Digital design process model proposed by Ohsuga et al. (taken from [13, 127]). 34

2.6 UI/UX design process (taken from [78]). . . . . . . . . . . . . . . . . . . . . 35

2.7 Smart space design framework (taken from [90]). . . . . . . . . . . . . . . . . 36

2.8 Traditional architectural design process (taken from [48, 50]). . . . . . . . . 37

3.1 Ethnographic study timeline. . . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.2 Ethnographic study. Left: Project 1. Right: Project 2 [161]. . . . . . . . . 50

xiii

3.3 Word-cloud from ethnographic studies— primary concerns, pain-points and

design solutions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

3.4 Perspectives of subject matter experts. Left: Focus group discussions. Right:

In-depth interviews. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

3.5 lumenHAUS [2]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

3.6 Design process diagram from ethnographic studies. . . . . . . . . . . . . . . 70

4.1 Framework development timeline (reproduced from Figure 1.4). . . . . . . . 74

4.2 Left: Traditional architectural design process. Right: Baseline framework

for smart home design. We adopted a color code scheme for different phases

where Yellow represents Schematic Design, Blue represents Design Develop-

ment, Orange represents Presentation & Evaluation, and Green represents

Construction (reproduced from [50]). . . . . . . . . . . . . . . . . . . . . . . 76

4.3 Iteration 1 of the proposed framework. . . . . . . . . . . . . . . . . . . . . . 79



4.6 Final Framework: Architecture and Technology in Smart Home DEsign (ArTSE). 85

4.7 IDEFo’s graphical format (adapted from [13]). . . . . . . . . . . . . . . . . . 86

4.8 The Ideation process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

4.9 Site analysis using 2D graphics (taken from [47, 48]). . . . . . . . . . . . . . 88

4.10 Using HCI models in smart home design [48] . . . . . . . . . . . . . . . . . . 89

xiv

4.11 Concept sketch of a web-based “Design your dream home” tool for clients/oc-

cupants for streamlining the design process. . . . . . . . . . . . . . . . . . . 90

4.12 The General Study process. . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

4.13 Schematic design example. Left: Activity based layout. Right: Smart tech-

nology inclusion with spatial layout . . . . . . . . . . . . . . . . . . . . . . . 94

4.14 From left to right: (a) Gesture-based UI using Kinect to control smart lights,

(b) MR-based UI, user’s POV (c) Voice command based UI, (d) GUI (OSRAM

Lightify app). [76, 77] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

4.15 Concept diagram of a tool for clients/occupants for vendor selection through

cost analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

4.16 The Development process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

4.17 Technology infrastructure consisting of three components [153, 155]. . . . . 102

4.18 The Implementation process. . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

5.1 Study setup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

5.2 Left: User interface showing time-series data depicting temperature, light,

energy consumption. Right: Web interface with MQTT publisher for con-

trolling different devices based on real-time data. . . . . . . . . . . . . . . . 118

5.3 Left: The Confusion Matrix generated by using seven minutes of the simu-

lated energy consumption signatures. Right: The Confusion Matrix gener-

ated using 15 minutes of the data. . . . . . . . . . . . . . . . . . . . . . . . 118

xv

5.4 The predicted value in blue compared to real value in orange. Top Left and

Top Right: Examples of true positive. Bottom Left: An example of false

negative. Bottom Right: An example of false positive. . . . . . . . . . . . 119

xvi

List of Abbreviations

AmI Ambient Intelligence

HCD Human Centered Design

HCI Human Computer Interaction

IoT Internet of Things

MR Mixed Reality

SBE Smart Built Environment

TBE Traditional Built Environment

xvii

Chapter 1

Introduction

Smart built environments (SBEs) are equipped with embedded technologies (sensors, actua-

tors, automated functionalities, etc.) [29, 35]. Hence, they are fundamentally different from

the traditional built environments and are equipped to provide functionalities like touchless

control, flexible space, energy efficiency, modular construction, home healthcare, etc. Smart

homes are one of the most studied SBEs, and they are considered the homes of the future.

The ongoing COVID-19 pandemic has enforced upon us a renewed dependence on our homes

for activities of daily living. As workplaces, educational institutions, and stores are closed

to contain the spread of the disease, a significant portion of the U.S. residents are forced to

be confined within their homes [28]. This new reality will have a lasting impact on how

we live and build in the future [25, 162]. Smart homes and architectural solutions can offer

an answer for this paradigm shift in people’s relationships with their homes [63, 80, 145].

Integrating advanced technologies within the built environment can significantly improve

our quality of life and reduce the burden of monotonous, time consuming work like cooking,

cleaning, etc. Technological interventions combined with spatial design solutions can also

be used to solve the issue of providing proper work/study space, exercise/activity zone, and

privacy within a fixed/confined space at home.

Sensors, actuators, and computation capabilities allow the objects in a smart environment

to be interactive and responsive to the user [48, 123]. The advanced technological capacity

also contributes towards achieving energy efficiency [133, 166]. The smart home concept

1

2 Chapter 1. Introduction

promises to improve the overall quality of life for the residents, assist an ageing society by

increasing independence and preventing emergencies, helps to manage energy consumption,

and provides safety and security for the residents [56]. Rapid innovation in related tech-

nologies for the past three decades and an exponentially increasing interest of the industry

in smart home devices bring new possibilities to the domain. Smart home research started

nearly a couple of decades ago, with projects like smart rooms by the MIT Media Lab (Pent-

land,1996) being pioneering works [55]. Other examples of smart homes are iRoom [91],

AwareHome [3], House n [86], GatorHouse [79] etc. Advancement of internet technologies

and Wireless Sensor Networks (WSN) has enabled Internet of Things (IoT) based smart

homes to conceptualize a smart, connected world since then [48, 146, 152]. Smaller, faster,

and cheaper computational devices connected via wireless devices are embedded in the sur-

rounding built environments like furniture, walls, etc. [90].

1.1 Background

In this section, we provide background knowledge on some central concepts for setting up

the context for this dissertation. We discuss traditional built environments (TBEs), smart

built environments (SBEs), and the comparison between TBEs and SBEs.

There are two types of built environments based on the building blocks, capabilities, and

characteristics— traditional built environments (TBEs) and Smart Built Environments (SBEs).

TBEs— TBEs consist of plain physical objects that offer basic interaction capabilities.

Interactions with these objects are isolated and primitive in nature. User needs to physically

move to a particular device for performing a task. For example, to control the oven, the user

needs to go to the kitchen [48]. The building blocks of traditional built environments can be

decomposed into two types of modular components: firstly, openings— like walls and floors

1.1. Background 3

Figure 1.1: Left: Two dimensions of traditional built environment design [48]. Right: Threedimensions of smart built environment (SBE) design [48].

and secondly, plain physical objects— like fixtures, furniture, and utilities [48, 90].

SBEs— SBEs consist of physical things that can sense users’ actions and emotional states

and respond accordingly. The objects are equipped with sensors (e.g., environmental, visual,

tactile, gesture recognition, etc.) and actuators to respond based on comprehended users’

actions [38, 48]. The smart objects equipped with computing, communication, sensing, and

actuation capabilities are referred to as “things” in IoT [22, 23, 117, 128]. Data collected

from the sensors is fed into digital systems that can change the state of smart objects using

actuators. By utilizing these sensors- and actuators-equipped objects, the user can achieve

many functionalities from any part of the environment. Hence, the functional boundary

between places in an SBE has blurred [48, 73]. For example, a user can control the func-

tionality of the oven from anywhere, she does not explicitly have to go to the kitchen for

this. Therefore, SBEs have a third dimension— embedded technologies, in addition to user’s

living requirements and the built environment (Figure 1.1) [48, 90].


Figure 1.2: Example of an SBE; Courtesy– Virginia Tech FutureHAUS [48, 161]

1.2 Motivation

Designing connected products and spaces is about designing the holistic experience for the

user. The user experience with the whole service, rather than just the technology or design

it offers, determines its value propositions. And in case of a smart home, user’s spatial

experience is a crucial part of it. In smart homes, the focus shifts from “artifacts” to “archi-

tecture” [6, 8]. Getting only focused on the technological concerns and forgetting about the

holistic user experience is a pitfall for IoT product designers. Smart home is a multidisci-

plinary domain that requires collaborative work from several disciplines like information and

communication technology (ICT), computer science and engineering, industrial engineering,

HCI, and last but not the least, architecture. In addition to sensing, networking, and actuat-

ing technologies, architectural design is also an important element to consider during smart

home design [6, 29, 50]. Wiberg et al. [164] discuss that as embedded interactive technologies

work as architectural elements, architecture is now a major concern for interaction design.

Hence, the technology element influences occupant’s activity flow and functional layout of

the SBE.

The inter-networking of the built components and everyday objects enables the “smart-

ness” of a smart home. Hence, the three primary elements of smart homes, i.e., embedded

1.2. Motivation 5

technology, architectural elements, and occupants’ needs, have significant impact on each

other [50, 90]. However, there is limited research on looking at smart home design from a

holistic point of view considering the inter-dependency of these three elements [9, 89, 90, 97].

In recent years, HCI researchers have started exploring people’s experience with built envi-

ronments. Researchers in Human-Building Interaction (HBI) give attention to human values,

needs, and priorities for addressing human interaction with built environments [9].

Despite the multidisciplinary nature of the smart home or smart living concept, the ever-

growing body of literature is dispersed and predominantly focused on isolated technological

aspects/innovation, improving cost efficiency, functional efficiency, sustainability, or spe-

cific application sectors [9, 148]. Till now the research and body of knowledge is mostly

focused on developing standalone technological solutions [3, 79, 86, 91]. Existing research

mostly emphasizes on solving engineering and software issues related to sensing, communica-

tion, computation/analysis, and actuation to provide rule-based automation [39]. Previous

works on developing frameworks for smart homes primarily focus on developing technologi-

cal frameworks for creating a collaborative network incorporating heterogeneous devices that

communicate with each other [39, 84, 104]. Some examples of prior research consist of in-

troducing protocols for user authentication [26], technological frameworks for programmable

Bluetooth devices [143], extensible application frameworks for dynamically adding clients

and services and integration of short-range devices [84].

However, integration of smart technology with the physical spaces changes the inherent ac-

tivity and usage pattern of a built environment [164]. In stark contrast with the traditional

environment with plain physical objects, SBEs provide a connected and responsive built

environment merging physical and digital world together. The situated interaction in every-

day life is mapped differently than a traditional built environment. Hence, integrating novel

technological solutions has the potentials to offer a paradigm shift in the spatial design of


a home. This can be illustrated by the evolution of kitchen design over the decades. New

technologies like microwaves, dishwasher and cooktops introduced drastic changes to activ-

ities like cooking and cleaning. This change in activity led to a change in usage pattern of

the physical kitchen space. In turn, that led to the evolution of kitchens from a separate

cook-only room to the central hub of the house consisting of an open floor plan and central

islands [29]. Another example of technological solutions impacting the spatial design can

be illustrated by the development of the “flexible space concept” enabled by reconfigurable

and responsive architecture. Incorporating actuators, motors, and sensors with architectural

elements like walls, partitions, furniture, etc. enables digitally controlled movement of these

elements. Which in turn allows the design of flexible spaces where walls/partitions can be

moved so that a single space serves multiple activities like entertaining guests, home office,

family living, etc. These exemplify that the integration of smart objects with the traditional

environment has the potential of dramatically changing the usage pattern and spatial design

of the space. Hence, innovative design solutions require consideration of both technological

and architectural aspects.

This motivates us to expand the scope of design thinking and explore perspectives from

related disciplines like architecture, HCI, HBI, building construction, computer science and

engineering. We explore this nascent research area where technology, architectural and

user-centered aspects come together to promote innovative solutions in smart home deign.

For designing better smart homes, we explore an architectural perspective along with its

technological counterpart. It is beneficial to learn from a discipline like architecture which

has a long history in building three-dimensional spaces made for people and everyday life.

1.3. Problem Definition 7

1.3 Problem Definition

Our previous discussion, in Section 1.2, suggests that we need to incorporate the archi-

tectural perspective with technologically driven design thinking to enable innovative design

solutions for smart homes rather than only focusing on the embedded technology. Disciplines

of architecture and urban planning have been significantly less involved with smart home

research, even though the professional responsibility for designing and implementing smart

homes and smart cities falls upon them [29]. Moreover, there has been little work on devel-

oping a comprehensive design process for SBEs. As there is no established framework for

the smart environment design process, current design and construction practices overwhelm-

ingly follow a mostly linear design and delivery approach [4, 90]. In this linear approach, the

physical infrastructure design and technological infrastructure design are considered as sep-

arate design activities. Designing computational capabilities isolated from the space results

in superficial design solutions [48, 90]. Usability engineering practices also suggest using

combined approaches to facilitate design components to work as a unified whole.

There are far too many examples of design fails because of the lack of a unified approach

that considers the physical space and users’ preference along with technological efficiency

[4, 113]. In many cases integration of smart systems make the buildings energy efficient but

lack of focus on the users made it uncomfortable for the occupants [4]. Smart “things” are

capable of changing the state of the built environment, so a carefully curated design process

integrating smart capabilities and traditional architectural design processes is necessary to

avoid any harm to humans [48]. Having a clearly defined framework helps the design team

to have a clear idea of necessary steps. Occupants’ activities of daily living, user–to–user and

user–to–device relationships, spatial design, physical and mental well-being, among others,

need to be considered for avoiding superficial and needless technological interventions and un-


informed spatial design solutions. Defining a process for SBE design considering its unique

characteristics is crucial. There exists a gap in design thinking in the form of a unified design

framework for SBEs. Hence, we need to develop a smart home design framework combining

the three smart home components to assist designers in avoiding these pitfalls.

The primary challenge in defining a smart home design framework is that there are many

issues associated with a smart home design process. TBEs focus on two components— the

user and the physical environment (Figure 1.1 (Left)) [48, 90]. Hence, traditional design

process focuses on the physical environment design, namely, designing the architectural di-

mensions and spatial quality based on user needs. On the other hand, in addition to the

physical elements, smart homes consist of ubiquitous computing technologies embedded into

the modular building blocks. The additional capabilities of smart homes have significant im-

pact on resident’s activity and spatial usage pattern (Figure 1.1 (Right)) [48, 50, 90]. Hence,

a smart home design process/framework needs to incorporate considerations for designing

the following components:

• Built environment - Building elements like wall, floor, openings, etc. are embedded

with sensors and actuators [48, 90]. Smart windows provide shading, light and pri-

vacy. Smart walls act as interaction interfaces and if they are movable, they facilitate

adaptable interior geometry of a space based on users’ needs [72].

• Associated technology - Smart MEP (mechanical, electrical, plumbing) systems are

crucial technologies for a smart living. Sensors, actuators, wearable devices etc. enable

the smart systems. Furniture like tables, mirrors, etc. are enabled with touch screen

functionalities. Fixtures like water closets are also equipped with smart technology [48,

90]. Other smart devices like smart fridge, smart meter, smart security system, etc

are incorporated with a smart environment. Smart lighting and appliances impact the

1.3. Problem Definition 9

comfort and quality of living.

• Living requirements - Safety, security, comfort, efficiency, preference, etc. are the user

centric aspects of smart home design [48, 90]. Occupant’s daily rituals and sense of

comfort are important considerations to ensure a successful smart environment design.

1.3.1 Research Questions

We define the problem scope of this dissertation in terms of the following three research

questions.

1. What are the issues related to smart home design?

2. What is the current state of the smart home design process?

3. How to define a design process/framework for smart homes that addresses both the

technological and architectural aspects based on occupant’s needs?

4. How to disseminate the framework and apply it in an SBE project?

1.3.2 Goals and Objectives

Through this dissertation, we aim to bridge the gap in design thinking for smart homes by

applying perspectives from architecture, HCI, HBI, and computer science and engineering.

Consequently, we also want to formulate a unified framework for smart home design, where

we will address both the architectural and technological design aspects within the framework.

While our study is mostly focused on the category of smart homes, but our goal is to develop

a generalized framework so that it can serve as a baseline for designing other types of smart


built environments. The future of built environments is SBEs and we hope this research

helps designers in the design process for reimagining the smart home and SBEs in general.

Goals and Objectives:

1. Rethinking smart home design by integrating technologically-driven design thinking

and architectural practices.

2. Developing a holistic smart home design framework through integrating issues of ar-

chitectural design and technological design.

3. Increasing the usage of smart built environment approaches in the residential building

sector by providing a guideline about the components related to smart home design.

4. Being a catalyst for a paradigm shift in design thinking in the smart home domain by

redefining the boundary between architectural design and smart technology design.

1.4 Research Approach

We summarize our research approach in Figure 1.3. We used the triangulation method for

conducting our research. The triangulation method refers to “a qualitative research strategy

to test validity through the convergence of information from different sources” [158].

Research question 1 is designed to discover various issues related to the smart home design

processes. To find the answer to this question, we conducted a literature review of IoT-based

smart homes. Our review consisted of addressing technology aspects, spatial elements of built

environments, architectural concerns, design challenges, use cases, and user-centered design

practices. Based on the review, we identified a potential research gap in the existing literature

1.4. Research Approach 11

Figure 1.3: Research approach

and discussed about the holistic smart home design process introducing architecture as an

important element.

We have also recognized that the smart home design process lacks an existing, well-defined

design framework. To develop such a framework, we reviewed different design processes of

different domains like– the traditional architectural design process, UI/UX design process,

digital design process, etc.

We posed the research question 2 to investigate the current state of the smart home design

process using the data source triangulation method [158]. Here we gain multiple perspectives

from individuals, focus groups, and SBE projects. We conducted this investigation through

a literature review on current research, ethnographic studies [83] and collecting opinions of

subject matter experts (SMEs). Timeline for focus group studies, interviews, and Delphi

studies is depicted in Figure 1.4. During the ethnographic studies, we have explored the


Figure 1.4: Timeline for focus group studies, interviews, and Delphi studies.

design processes by being involved in the design process of two smart home projects— the

KACST project, and futureHAUS. From hereon we refer to them as Project 1, and Project 2.

The design teams of these two projects were led by subject matter experts (SMEs). They are

researchers and practitioners who have been involved in smart home research for decades.

We observed the design processes, issues, best practices, guiding principles, and decision

making criteria of SMEs during these ethnographic studies. The perspectives of SMEs were

collected through focus group studies and in-depth interviews. We conducted focus group

studies with the team members of the above-mentioned two projects to collect information

about the best practices, design processes, decision making criteria, and team structures.

We identified a nascent research area to reimagine smart home design and manufacturing

by addressing technological, architectural, and user-centered components. The discussions

with the SMEs introduced us to many unique and interesting ideas and brought up novel

approaches to address the issues of designing and developing smart homes.

We used the findings from our research questions 1 and 2 for answering the research question

3. We have reviewed related literature to learn about the design processes used in other

disciplines. Here we used the theory triangulation approach [158]. Different theories and

frameworks assist us in our process. Then we used the findings from the ethnographic studies

and perspectives of the SMEs to formulate a design framework. We finalized this framework

1.5. Research Contributions: 13

by reaching consensus through an iterative process using Delphi studies [82] with subject

matter experts. Delphi studies are used for gathering the convergence of opinions from a

group of experts on that domain.

For research question 4, we used a case study to explore the application of the framework and

develop an implementation strategy to get this in the hands of researchers and practitioners.

We identify potential issues with implementation through the case study.

1.5 Research Contributions:

In this dissertation, we have documented findings from our research aimed at answering the

research questions listed in Section 1.3.1. We have identified the issues related to smart

home design through an extensive literature review by exploring the technological aspects,

use cases, and architectural aspects of smart home design. Our review encompasses the

domains of HCI, SBE, and immersive technologies in this process.

We investigated and identified the current state of smart home design through gathering real-

world perspectives of researchers and practitioners from ethnographic studies, focus group

studies, and interviews. From the identified issues of smart homes and the current state of

the smart home design process, we made a case for a holistic smart home design framework.

Finally, we developed a framework, Architecture & Technology in Smart Home DEsign

(ArTSE), for assisting the smart home design process through an iterative process using

Delphi studies. The ArTSE framework includes necessary steps for co-designing the spatial

aspects and the technological aspects for smart home design. We base our development of the

ArTSE framework by extending our earlier efforts for developing a smart home design frame-

work [47, 48, 50]. In developing technological aspects of the framework, we have studied the


design and implementation of IoT-based ambient intelligent frameworks for SBEs [153, 155].

To that end, we have also explored how to design interactive and engaging user experiences

with digital systems and discussed multimodal interaction techniques for interfacing with

SBEs [52, 76].

We developed strategies for dissemination through a case study application of the framework.

We also formulated approaches for packaging the framework.

1.6 Dissertation Structure

This document is organized into seven chapters. Chapter 1: Introduction presents an

overview of the domain and motivates the research. This chapter also defines the prob-

lem and formulates the research scope for the dissertation along with providing a summary

of the approaches to develop the intended framework. Chapter 2: Literature Review provides

an overview of smart homes and related research. It also reviews the design processes from

other domains. Chapter 3: Understanding the State of the Art of Smart Home Design Process

presents the extracted information from a set of ethnographic studies, focus group studies,

and in-depth interviews. Chapter 4: Iterative Development of a Smart Home Design Frame-

work describes the development and consensus of the ArTSE framework for smart home

design. Chapter 5: Technological Aspects of the ArTSE Framework provides a synopsis of

our research on the underlying technology that enables an SBE. Chapter 6: Dissemination

explores dissemination strategies through the application of the proposed framework to a

case study. This chapter also discusses the overall contributions of the research. Chapter 7:

Conclusion provides the conclusion and future directions.

Chapter 2

Literature Review

The goal of our literature review is to explore the existing literature to understand the issues

associated with a smart home, to identify factors that impact the smart home design process,

and cover the different design processes from other domains to guide us in developing our

framework. A smart home is a residence where everyday objects are embedded with com-

munication and computation capabilities. A smart home is able to provide context-aware

services and monitor the energy usage, safety, and well-being of the occupants. Recent in-

novations and exponentially growing interest from the industry brings in new possibilities to

the domain. The smart home design process includes technological design and architectural

considerations. We reviewed various principles and aspects of IoT-based smart home design

to understand the different practices, architectural components, and technological compo-

nents of the smart home design process. We first looked at the components of smart home,

the current focus of smart home research in the field of computer science and engineering, the

current state of HCI and HBI research, the missing architectural aspect, the motivation for

discussing the architectural aspect, and the need for a framework. We also explored the re-

quired information for developing a framework, and the frameworks used in other disciplines

to use as a baseline.

15

16 Chapter 2. Literature Review

2.1 Review Methodology

Three types of publications were identified (Table 2.1). Firstly, publications related to

the use cases and technology aspects of smart home. Secondly, publications related to the

architectural aspect of smart homes, HCI, and HBI. Thirdly, the existing literature on design

processes from other disciplines as there is no existing framework for smart environment

design.

Search Strategy

We have explored peer-reviewed literature and scientific reports published in the English

language. To cover not only the technological aspects but also the architectural and design

issues, the search was conducted across disciplines in the following databases: Scopus, IEEE

journals, Science Direct, Architectural Science, ACM Digital Library, Journal of Information

Science and Engineering, Google Scholar etc.

Inclusion Criteria

The smart home review search produced 811 results in Scopus. Architectural design process

search produced around 1590 results in Architectural Science Review. Searches in Google

Scholar for architectural design & HCI, and architectural design & HBI produced thousands

of results. We have sorted them by relevance and looked at the research since the year 2000.

We have also used some forums and online discussions specifically for gathering information

about architectural processes. We mostly sorted through the papers in the following ways -

most cited, most relevant, and the most recent papers.

2.1. Review Methodology 17

Types Clusters Topics

Type I:Overview ofSmart HomeDesign andResearch

Application Areas

Energy ConservationHome Healthcare

Security and Safety MonitoringEntertainment and Comfort

Smart Technologies

IoT TechnologiesSmart Houses

Network ArchitectureData ModelData Analysis

Services and ApplicationsEdge ComputingUser Interaction

Security and Privacy

Type II:Architectural,HCI, and

HBI Concerns

Smart Home, Architecture,Construction

Spatial Elements of BuiltEnvironments, Architectural Concernsfor Smart Homes, Industrialization ofManufacturing Process, Prefabricated

ArchitectureSmart Home and HCI Sustainability and Energy

Optimization, Privacy and Intimacy,Rituals and Social Practices, Domestic

IoTSmart Home and HBI Physical, Spatial, and Social Aspects

of Interactive Built Environments

Type III:Design Processes/Frameworks

AcrossDisciplines

Design Theory Architectural Design Principles,Pattern Language

Design Processes Digital Design Processes, TraditionalArchitectural Design Process, UI/UXDesign Process, Smart Space Design

Process

Table 2.1: Table illustrating the topic areas covered by this literature review.


Keywords

The keywords used here are “review OR literature AND smart home”, “smart home AND

IoT”, “home AND automation”, “architectural design process OR principles OR methods

OR frameworks”, “smart home AND architecture”, “architectural design factors OR the-

ory”, “interactive architecture”, “smart space AND design”, “human perception”, “human

behavior pattern AND smart home”, “HCI AND smart home”, “HBI AND smart home”.

2.2 Overview of Smart Home Design and Research

This section describes an overview of current smart home research and practices. Technolog-

ical innovations to enable these application areas are the main goal of research in Computer

Science and Engineering. A smart home designer/design team needs to know about the

focus of the existing research and practice from the perspectives of purpose and prospective

applications.

2.2.1 Goals and Research Focus

Current smart home research and technological innovations focus on energy conservation [5,

92, 148], construction and maintenance safety [55, 65, 114, 159], home healthcare, e-health

and ageing in place [35, 36, 56, 88, 100, 102, 131], and comfort and assistive technology [56,

66, 98]. Disciplines of architecture and urban planning have been significantly less involved

with smart home research [29]. Initially, smart home research mostly focused on improving

the quality of life, energy saving, and providing security [35]. Now, smart home applications

are increasingly getting more focused on the control of smart home systems and support for

the elderly and people with disabilities.

2.2. Overview of Smart Home Design and Research 19

• Energy Conservation: Functional monitoring and remote management of IoT devices

enable reducing energy wastage [5]. Energy providers are focusing on smart energy

applications where water and energy consumption data (electricity, gas) can be moni-

tored remotely by the users and the utility company [148]. HVAC systems, electrical

appliances and door/windows can be automated or remotely controlled based on out-

side temperature [5, 35]. Occupancy detection, remote control, quality monitoring,

rescheduling operating time based on demand, etc. are useful for significant impact on

energy conservation [55]. For example— wireless speakers for appliance control and

smart thermostats are very popular smart home devices in the US.

• Home Health-care: Home health care can be divided further into three categories:

eldercare, healthcare, and childcare [55]. According to the current population trend,

by 2050, 20% (approx.) of the world population will be at least 60 years of age [35].

For catering to the needs of this ageing population, detecting occupant’s actions and

health conditions allow smart homes to support well being of residents. Home automa-

tion technologies enable supporting aging in place, deferring institutionalizing elderly

people, and reducing medical costs. A smart home can help monitor and assist elderly

and disabled persons [35]. Sensor networks connected to smart devices allow elderly

people suffering from chronic illness to get the necessary monitoring in their own home,

which reduces overall medical expenses [148]. Wearable monitoring technologies and

assistive robotics in the context of a smart home are also explored to monitor elderly

and disabled people [33, 35, 131]. Chan et al. discuss wearable monitoring technologies

and assistive robotics in the context of a smart home [35]. Patel et al. discuss the

application of wearable technology to monitor elderly and disabled people [131].

• Security and Safety Monitoring: Wireless security systems, occupancy detection sys-

tems, and security cameras are used to provide safety and security by providing dis-


tance surveillance [148]. Information is extracted from processing surveillance data to

raise alarms in case of burglary, theft, and natural disasters like flood, etc [55].

• Entertainment and Comfort: The home can become an entertainment experience and

gaming center with services from telecommunication and content providers [148]. Voice

assistants (e.g., Amazon’s Alexa, Google Home, etc.), smart TVs, smart speakers, video

conference options, etc., are just a few examples. Cognitive support or sensory aid

technology can also increase comfort in the home environment. Automated or self-

initiated reminders like medication reminders, management tools, lost key locators,

verbal instructions for using an appliance, etc., are examples of such technology [56].

• Increase Social Interaction: Another focus of smart home research is increasing social

interaction. Video based communication with friends and family, virtually participat-

ing in group activities, etc., are some examples of such technologies [56].

2.2.2 The Underlying Technology that Enables IoT-based Smart

Homes

In this section, we provide a comprehensive overview of the technologies and techniques that

enable IoT-based smart homes. The layers associated with the smart home technology stack

for developing an IoT framework are– data collection using sensors/devices, data transport

through network and storage, data analysis, services and application, and user interface [27]

(Figure 2.1). Hence, the system architecture includes— collecting the sensor data, trans-

porting and storing them in a central system, and analyzing them to program services and

applications [48] (Figure 2.2). The layers of the technology stack are briefly described below:


Figure 2.1: Layers of smart home technology stack.

Data Collection Layer

Data is collected using sensors or devices. Recent advances in sensor technology (i.e., cheap

and small wireless sensors, RFID tags, etc.) and communication technology have opened

new possibilities for smart homes [35, 131].

Different types of sensors used in SBEs are [48, 50]:

1. Location sensors: Used for detecting human presence using IR motion sensors, pressure

sensors, optical and magnetic sensors, etc., when they pass through detection zone. A

more direct approach is spotting the person using video cameras, even though privacy

is compromised in this case [35].

2. Mobile sensors: Sensors that are used for identifying gesture, motion, etc.

3. Environmental sensors: Sensors that can measure humidity, temperature, etc.

4. Wearable sensors: Sensors that can be attached to wearables, i.e., garments (shirts,

socks, etc.) or accessories (glasses, jewelry, watches, etc.) [29].


Figure 2.2: System architecture example (reproduced from [48, 50]).

Network Connectivity and Data Transport Layer

Connectivity is the cornerstone of a IoT-based smart home [15]. Recent advances in com-

munication technology as in the availability of personal computers, GPS enabled cellular

phones, efficient network devices, and protocols have created new opportunities for smart

homes [35, 131].

For designing an efficient indoor wireless sensor network, a detailed description of the building

environment is necessary to predict the signal propagation and the quality of the link between

sensor nodes [75]. The goal of an IoT is to develop elements on top of the internet to enable

the process of tracking items and sharing information easier [151]. Kelly et al. [94] presented

a self-control mechanism for better operation of the devices using an integrated network

architecture and interconnection.

Data Storage Layer

Once the data is collected, it needs to be stored in a meaningful and organized way to

facilitate management and operation. Integration of BIM in the smart home design process

can be useful for user-centric smart services design [166]. BIM can also be extended to


include smart object profiling. There are two aspects of smart home design and management

: service and sensing. The service aspect supports users in their daily lives. The sensing

aspect focuses on the application of sensor-based models to the design of smart spaces.

Lertlakkhanakul et al. [108] developed a data model simulating the smart home services. The

web-based digital representation of places and users enabled visualization of invisible services

and the configuration of smart capabilities. The proposed method focuses on increasing user

participation in the smart services design process.

Data Analysis Layer

The data collected from the smart home is used for monitoring, analyzing, and forecasting.

Doyle et al. [61] discuss about the necessity of assessing everyday aspects of well-being of

older adults in a home-based self-management system. Several data analysis techniques are

used to decide when to trigger an alarm or perform a reactive action. There are different

techniques used for activity detection, i.e., audio-based techniques, audio-visual techniques,

sensor-based techniques, and a mixture of all these techniques [55]. Smart homes produce

a lot of data from heterogeneous sources, where some of the data can be imbalanced. They

require special algorithm techniques to make proper inference and prediction. Analytical

prediction algorithms using neural networks, Markov chains, machine learning, predictive

algorithms, decision trees, probabilistic models, classification, clustering, etc. are commonly

used for decision making [35, 53]. For these techniques to work, it is important to identify

and learn from a lifestyle pattern of residents defined by consistent habits. A collection of

conditions can be devised by learning from user behavior patterns [160]. The analytic system

should also be robust enough to address deviations from habits like vacations, etc. [35].


Services and Application Layer

This layer uses analysed data for controlling and monitoring the building’s conditions using

chain reaction rules and API. Context-awareness in smart homes means that IoT devices need

to do more than just sense the current state of their environment. Such devices must also be

able to respond to and influence the state of their surroundings, based on predetermined or

learned parameters. The Gator Tech Smart House [79] is an example of this type of context-

aware spaces. There are sensors paired with actuators that trigger state changes when certain

conditions are met. The state changes are defined using ECA (event, condition, action) rules.

Different events trigger different services [85].

Makonin et al. [112] explored four case studies on an ambient intelligent environment. The

results from the case studies show that a rule-based system for ambient intelligent environ-

ment is infeasible and a fully automated approach is more cumbersome for the users.

User Interaction, Interfaces, and User Experience Layer

In a smart space, everyday objects work as dynamic interfaces. So the boundary between

physical and digital spaces starts disappearing. This change in the nature of HCI requires

well-defined interaction design which is not a cognitive burden to the users. Mapping between

action and perception needs to be natural to help users feel comfortable in a space. [48, 90].

There are two types of interaction modalities:

1. Explicit interaction– physical switches, input devices like smart phones, remotes, etc.

2. Implicit interaction– gesture-based interaction, voice-based interaction.

A balanced and multimodal interaction design which leverages both explicit and implicit

interaction is ideal for providing a comfortable user experience.


IoT-based Ambient Intelligence

Augusto et al. [24] define AmI as “a digital environment that proactively but sensibly sup-

ports people in their daily lives.” There are many research efforts related to smart home

monitoring systems, such as the Gator Tech Smart House [79], Casas Smart home [41],

Georgia Tech Aware Home [96], and Place Lab [87]. Most of these efforts were focused

on specific purposes, such as information collection and decision supports for occupants,

surveillance, storage and retrieval of multimedia data. Interconnected communication be-

tween every day objects is necessary to facilitate such environments, which can be achieved

by IoT. The layers associated with an ambient computing technology stack for developing

an IoT framework are sensors/devices, network connectivity and data transport, analytics,

API, and user experience/interfaces [27].

Kelly et al. [94] presented an integrated network architecture and interconnection mechanism

for collecting parameters from smart sensors. Doyle et al. [61] discuss about the necessity

of assessing everyday aspects of wellbeing of older adults in a home-based self-management

system. While considering a IoT-based AmI system for SBEs, it is important to consider

the challenges and opportunities related to context awareness, safety, security, and privacy.

Context-awareness means that IoT devices need to do more than just sense the current state

of their environment. Such devices must also be able to respond to and influence the state

of their surroundings, based on predetermined or learned parameters.

Edge Computing

In the case of edge computing, datakkoa storage and computation are brought closer to

the source of data. Safety of smart home residents must be supported by adequate IoT

communication mechanisms. [67] propose a biologically inspired approach to modeling safety


protocols for hazard detection in smart homes. Their approach leverages edge computing

to imbue IoT devices with decentralized decision-making capabilities in order for them to

make rapid decisions to prevent safety hazards that may involve home inhabitants. For

making rapid contextual decisions, a cloud-based system infrastructure that relies on a strong

network connection may not be sufficient [12].

2.2.3 The Spatial Elements of Built Environments

We get an overview of the generic elements of built environments by reviewing architectural

design theory [30, 48]. The modular components discussed above are used as building blocks

to design these elements in a built space. The taxonomy of spatial elements that define the

quality of a space is discussed here based on the works of Norberg-Schulz, Lynch, Thiel and

Mitropolos [37, 111, 119, 125, 156].

• Places - A Place is where an activity is carried out. A place has a defined boundary

where “inside” and “outside” are clearly defines [125].

• Paths - A path has a starting point and a defined course which leads to a destination.

A path encourages movement and provides a sense of direction [111].

• Domains - Domains are well-defined areas that consist of multiple places and a system

of paths connecting them. According to Schulz, domains or districts are unstructured

grounds and “places” and “paths” are the components of a domain [111, 125].

• Threshold - Thresholds are the defining edges of the elements of a space, for example,

the connecting point of two paths [125].

• Objects - Objects are the elements in a space that establish the characteristics of a


Figure 2.3: Different elements of building systems (reproduced from [13]).

space [37]. There are different types of objects based on different defining characteris-

tics. For example:

Based on form – surface/planar objects, three-dimensional objects.

Based on function – edges of a spatial form, points of reference, furniture, fixtures,

construction materials like brick, concrete, building elements such as walls, columns,

floors, etc.


2.2.4 The Architectural Concern for Smart Homes: Contempo-

rary HCI, HBI, and Architectural Research

Contemporary HCI literature addresses the smart home from various perspectives of sustain-

ability and energy optimization, privacy and intimacy, non-human and machine agency, rit-

ual and social practices such as doing laundry and gardening, domestic IoT and so on [44, 99].

Here space is a direct element of design and spatial context defines the interaction scenario [6].

As evident from these research, the spatial and temporal contexts, in which smart homes are

operationalised, are crucial components for smart home design. Hence, smart home research

needs to incorporate an architectural analysis. On the other hand, architectural research

also celebrates the incorporation of digital elements into built environments and its poten-

tial to redefine the future of architecture [149]. Relevant research elaborates on the influence

of computer networks on how we live, work and move just as railroads influenced settle-

ment patterns of the 19th century [6, 118]. Researchers in the architecture and construction

industry started exploring the industrialization of the smart home manufacturing process.

Prefabricated, off-site construction provides added benefits to the smart home designers for

integrating smart technology.

The different elements of building systems are shown in Figure 2.3 [13]. Embedding com-

puting technologies with these elements enable smart functionalities in smart homes. If the

architectural component of smart homes is overlooked, it results in superficial smart home

design solutions reducing the adaptability of the space to meet users’ needs [48, 90]. Smart

home design needs to become an unified process rather than an isolated engineering prob-

lem or an architectural problem. Smart device functionalities are affected by the spatial

design [141]. Hence, architectural measurements are crucial while installing IoT devices.

Moreover, the overlaying of interactivity onto the built environment can have impact on


the spatial design of the built environment itself. The restaurant in Umea, Sweden, is a

good example of this [164]. The architectural layout of this restaurant defies the regular

norm because it is designed based on smart functionalities that changes the activity flow

of customers. Integrating ubiquitous computing, IoT and embedded technology with any

activity or space effectively redesigns the activity pattern of the users and thus redefines

the flow diagram for spatial layout. Therefore, combining interaction design and architec-

tural design practices together would be helpful for integrating interactivity into the built

environment. The study of ubiquitous computing demands combining the study of tangible

interfaces and interactive behavior together [60]. In ubiquitous computing, “the world is

the interface” [163]. Hence technologies preferably recede in the back. The UbiComp the-

ory embraces utilizing our natural skills and activities where the smart devices merge with

the activities. So, the design concern is how to incorporate contextual factors to assist in

meaningful actions.

HBI is another collaborative area that addresses the physical, spatial, and social aspects of

interactive built environments. HBI research is beginning to address issues like compatibil-

ity of the technology design process with the architectural design process of buildings. The

architectural design process has a significantly longer lifespan compared to the technology

design process [6, 7]. HCI literature includes historical and gendered critique of smart homes

in books such as “smarter homes” [57] and “smart wife” [150]. These works do not explic-

itly address architecture, but take into account the spatial and temporal contexts in which

smart homes are operationalised. These works help motivate the argument for including an

architectural analysis in smart home research. Designers of connected products or smart

environments need to understand the human-to-thing interaction by studying the primary

users, stakeholders, and the effects of networked technologies [141].

Smart functionalities need an undisturbed communication level, regardless of the informa-


tion network being wireless sensor network (WSN) or wired Ethernet. The second important

aspect is how the smart device is interacting with the surrounding environment. In SBEs,

the space data, building floor plans, etc are important. Architectural design influences the

environmental efficiency of a built space, so smart devices that impact environmental factors

need to be considered based on their spatial context [166]. According to Zhang et al. [166],

general challenges in smart space design include how the smart device is incorporated with

the environment. The sensor effectiveness significantly depends on the location and the sur-

roundings. For example, the measurement readings of ambient light sensing or temperature

sensing would depend on locating the sensors near the window or fireplace. Hence, while de-

signing the data collection layer and layout of smart devices and sensors, the spatial context

needs to be considered properly.

Overall, the effect of a smart object in a smart space is determined by its position in the

space, capability, interactivity, autonomous behavior, and interaction modalities. Mapping

the pattern of smart objects with the spatial design and interaction scenarios of everyday

life is the challenge faced by designers of smart homes. According to Jeng et al. [90], the

architecture can become the interface for humans to interact with in a smart space. Modular

building components embedded with smart technology can be used to compose the smart

space and facilitate smart living.

So from the above discussion, we can say that, in case of a smart home user interaction and

activity patterns are fundamentally different and unique from a traditional home because

of its enhanced capabilities. This unique capability needs to be reflected in the functional

layout of the smart home to ensure a successful design. Contrary to a traditional home

designer, a smart home designer needs to follow a multidisciplinary approach from the very

beginning of the design process addressing the interplay of the three elements– embedded

technology, architectural elements and interaction modalities [50]. However, current smart

2.3. Guiding Principles and Techniques of Design Processes 31

home design practices address these three elements as separate processes. And existing

research focuses mostly on standalone technological aspects. Consequently, spatial designs

fail to fully address the smart capabilities to enhance users’ overall spatial experience or

impact activity patterns and lifestyle.

2.3 Guiding Principles and Techniques of Design Pro-

cesses

Smart home design process needs to address the inter-dependency of three elements– em-

bedded technology, architectural elements and interaction-modalities. Currently there is no

well defined design process for smart home design. Consequently, smart capabilities are not

fully utilized to enhance users’ overall spatial experience or impact activity patterns and

lifestyle. Hence, in this section, we review design theory and principles and explore existing

design processes for defining a smart home design framework.

Traditional Design Principles — Traditional architectural design principles can be con-

sidered as a foundation for smart home design. We explored how people use built envi-

ronments and what shapes the spatial planning for humans and perceived how this design

considerations can influence the design philosophy of environment and interaction design in

the smart environment. Alexander et al. [11] discuss a comprehensive set of guiding princi-

ples or patterns for designing integrated and human centered spaces based on comfort and

functional units. The primary considerations of occupants, public/private zoning and func-

tional zoning guide the design process. They emphasize on physical and social relationships,

user-to-built spaces and user-to-user for human centered design. Allen et al. [14] discuss the

risk of creating a sense of conflict by uneven implementation of modern technologies in the


context of urban design. Similarly there is an equal risk of losing identity and sense of place

by over-enthusiastic implementation of technology in the context of smart home. On a simi-

lar note, Sibyl [120] criticizes the “scientific” approach of trying to create a universal module

for city design. A robotic grid without respecting the different context, culture, geography,

socio-economic and political state, gives rise to inhuman urban conditions, creates lifeless

cities. Similarly, there can be no ‘overall singular solution’ for smart home design [48].

2.3.1 Existing Design Processes as a Baseline for Smart Home

Design Framework

In this section, we discuss the design processes originated from different domains like archi-

tecture, digital design, manufacturing and assembly to guide us in developing a framework

for smart home design.

1. Traditional Digital Design Processes:

The traditional digital design process can potentially be a model or baseline for smart

home researchers for developing a holistic smart home design process. Despite many

attempts at mapping the design process, there is no one universally accepted descrip-

tion [13]. This process describes the stages of design process and includes the use of

digital design techniques within the design and manufacturing process.

Pahl et al. identify the four main phases of a design process and McMahon et al.

model these main phases [116, 130] (Figure 2.4):

(a) Clarification of the task— Design requirements and constraints information col-

lection and creating specification.


Figure 2.4: Steps of the digital design process proposed by Pahl et al., modeled by McMahonet al. (reproduced from [13, 130]).

(b) Conceptual Design— Determining which functions to include and identifying suit-

able solutions.

(c) Embodiment Design— Detail development of the conceptual solution and solving


Figure 2.5: Digital design process model proposed by Ohsuga et al. (taken from [13, 127]).

issues.

(d) Detail Design— Finalizing dimensions, materials and forms for manufacturing.

To move from one step to another, a decision needs to be made. If there is any concern

about the previous step, then feedback and redesign are implemented (Figure 2.4).

The design process model proposed by Ohsuga [127] identifies three main design

stages (Figure 2.5):

(a) Conceptual Design— Requirements collection, building model.

(b) Preliminary Design— Modifying and refining the model through evaluation and


Figure 2.6: UI/UX design process (taken from [78]).

analysis.

(c) Detail Design— Modifying and refining. Finally, generating information for plan-

ning, manufacturing and testing and producing the end product.

2. UI/UX design process— The UI/UX design process Figure 2.6 is an iterative pro-

cess consisting of four steps.

(a) Understand needs— Understand user work and needs.

(b) Design solutions— Create design concepts.

(c) Prototype candidates— Realize design alternatives.

(d) Evaluate UX— Verify and refine designs.

3. Smart space design process— A smart space design framework discusses three

dimensions of smart spaces Figure 2.7. Here, the spatial aspect, ubiquitous computing

technology and living requirements are the three dimensions [90]—

(a) Integration of Physical-Digital— Walls/ floors/openings, space, furniture, appli-

ances.


Figure 2.7: Smart space design framework (taken from [90]).

(b) Living— user’s preferences, health, safety, sustainability.

(c) Technology— Sensing and Perceptual, intelligent devices, networking.

4. Traditional Architectural Design Process:

There are four general stages in this process–

• Pre-design Information Collection Phase— Collecting requirements from clients,

information about the site and climate.

• Ideation Phase— Developing the schematic design solutions.

• Representation Phase— Presenting the schematic design to clients and other

stakeholders.

• Iteration Phase— Incremental development of the design after getting feedback

from the clients and stakeholders.

The RIBA design plan of the work mentions three main stages for the Design/Ideation

phase [43, 121].

• Outline Design Stage— Determining the overall design approach.

• Scheme Design Stage— Preliminary massing and spatial planning.


Figure 2.8: Traditional architectural design process (taken from [48, 50]).

• Detailed Design Stage— Functional design of the spatial layout, facade design,

and sectional design.

2.3.2 Discussion

In this section, we discuss our opinion about the smart home specific requirements within the

steps of the traditional architectural design process informed by our review of the various

design processes. The comprehensive outline of the traditional architectural design pro-

cess (Figure 2.8) [48, 50] is built upon discussions about the architectural design process in

related literature [34, 50, 54, 58, 95, 115, 121]. We have elaborately discussed the additional

activities that the designer would need to perform for designing a smart home within each

step.

• Step 1 — Program Analysis: At the beginning of a project, the designer needs to

define the problem by analyzing the use cases in addition to the required program to

understand the functionality requirements of the physical space, usage pattern, client’s


perspective, etc. The traditional analysis focuses on the physical dimensions and the

traditional use pattern.

Observation — In the case of a smart home, analysis of the program needs to be done

considering an additional layer of ecological factors, networking infrastructure of the

area, socio-cultural factors, third party smart application developers, etc [141]. Identi-

fying users’ requirements and preferences are also essential for a successful smart home

design. Leveraging the HCI models discussed before can be useful for the designers in

this case.

• Step 2 — Site Analysis, Contextual Information: The next step is to collect

the necessary information about the site and analyze the context, topography, and site

forces like views, wind direction, and sun path.

Observation — Operational context is particularly important for smart home design.

Because a smart home designer will need to provide different solutions for a different

set of constraints for different contexts, i.e., wilderness, urban areas, and rural areas

(e.g., unhindered Internet access, power supply, etc.).

Step 3 — Concept Development and Schematic Design: In this step, a concept

is developed for the physical layout of a home based on a feasibility study. It depends

on the user’s lifestyle, activity pattern, and cultural preferences. This step includes

design analysis and different options for diagrammatic solutions to functional and

circulation problems, space layout, massing, construction, and cost appraisal. Energy

consumption simulation based on glazed facade, building shape and room functions

can also be useful in this step [121]. The process consists of drawing a flow diagram

and activity diagram.

Observation — In the case of smart homes, developing a scheme for smart capa-

bilities in this step is crucial. A balanced scheme consisting of learned automation,


programmed automation, fully automatic, and user-initiated actions needs to be de-

veloped depending on the user’s preferences. A fully automated system can become

overbearing for users where they do not feel “in-control” [141]. This sort of situation

may even lead the users to completely abandon the automation as evident from the

example of the North House [113].

• Step 4 — Design Development: This is the detailed design step once the client

approves the proposed outline from the previous step. The design phase consists

of developing the site layout, spatial arrangement, form of built structure, elevation

treatment, structural design, interior design and material preference, construction and

environment systems [121]. 3D CAD, Revit, SketchUp, etc., software are used as design

and modeling tools.

Observation — In the case of smart homes, architectural components work as inter-

action modalities and smart objects function as architectural components. Planning of

the layout of smart components, sensors, actuators, and meters need to be integrated

into the architectural design process of smart homes. Hence, the designer of a smart

home needs to develop a system architecture addressing all components. A system

architecture is an integrated platform consisting of software and physical elements

that controls the whole system, making the smart home responsive to a changing en-

vironment. Sensors and actuators send data to a server, an application accesses the

data and determines the role and behavior of smart devices. Data analysis tools help in

improving the building performance. There are three layers in the system architecture:

1. Spatial system - Spatial planning of the environment and designing controllable

or movable physical components [72].

2. Sensor networks - Collecting environmental parameters like temperature, humid-

ity, etc. and designing the sensor network.


3. Services and Application layer - Using collected data for controlling and moni-

toring building’s conditions.

Embedding the sensors or actuators within the building components would potentially

change the construction detail of those components, so understanding the material

properties, sensing technology, etc. is necessary for the designer to avoid potential

hazards. Another important design issue is choosing smart appliances, HVAC (heating,

ventilation, and air conditioning) systems, lighting, etc from the existing off-the-shelf

solutions and maintaining inter-operability among the whole system.

• Step 5 - Presentation and Evaluation: Computer drafting, drawing, and 3D

models are predominantly used for the development and presentation of architectural

ideas [30]. But these tools have limitations in the case of smart home design.

Observation — Novel immersive simulation techniques can assist in evaluating the

enhanced smart home capabilities and as input-output modality. Gračanin et al. [69,

70] describe an approach to modeling a virtual reality digital twin of a smart space that

can be used to understand the affordances of the physical space. Reconfigurable spaces

can be simulated to understand the capability and spatial impact [50]. An immersive

platform has potentials for remote and in-situ collaboration with other consultants.

Incorporating editing capabilities within the immersive platform allows the designer

to make the necessary changes and test different iterations of the design at different

scales [18, 144]. This technology can reinvent the architectural/smart home design

process.

• Step 6 - Improve the Design and Iterate Back to Step 1: The next step is

to improve the design based on the feedback from stakeholders. This is an iterative

process, which might require going back to step 1.


• Step 7 - Detail Development and Construction Documents: Once the design

is approved, the next step is to design the details and create construction documents

for coordinating structure and service installations. Construction documents include

working drawings and specifications for guiding the construction. Energy simulation

techniques can be useful in this step to modify the details for making the building

more energy efficient.

Observation — In the case of smart homes, this step needs to consider integrating

additional technology to support the requirements of smart homes. Embedding sensors

and actuators in building components would need to be carefully detailed in drawings

and models to avoid potential hazards. Understanding the effect of smart components

on construction materials is also an important issue.

• Step 8 - Bidding and Construction phase: The construction documents are

used for bidding to select a contractor. Then the construction phase begins and the

architect oversees the construction and interprets changes.

Observation — In the case of smart homes, this step needs to be a more multidis-

ciplinary approach. Architects, computer scientists, interaction designers, civil and

electrical engineers need to work together to develop a successful smart home.

In summary, the traditional process focuses on the physical objects, dimensions and the

traditional use pattern, which is not enough for smart homes. Smart homes need a more

detailed focus on operational context, users, and technology to provide a seamless user

experience. A framework for smart home design needs to include processes to assist in

designing the interdependency between smart objects and interaction scenarios.


2.4 Other Concerns for Smart Home Design

While implementing an IoT-based smart home system, it is important to consider the chal-

lenges and opportunities related to context awareness, safety, security, privacy, usability,

affordability, interoperability, standardization and collaboration [15, 148]. We discuss some

of these issues in this section.

Interoperability — Sensors and smart objects are connected using different communi-

cation networks and protocols in a smart home. An IoT enabled smart home is equipped

with a large number of heterogeneous devices from different vendors [15]. Most of the

devices have varying standards and limited computing and network capabilities. It is a chal-

lenge for a smart home designer to design a system architecture that allows interopeability

of heterogeneous devices. As a solution, the implementation of a middleware provides ob-

ject virtualization and standard interfaces. Middleware supports object abstraction, service

management, and service composition for creating complex services [23]. Tasooji et al. [153]

describe a multipurpose IoT framework for an ambient intelligent environment consisting of

data collection, data storage and data analysis layers. Web services and Simple Object Ac-

cess Protocol (SOAP) can also be used to solve this issue. Open Services Gateway initiative

(OSGi) is also another probable approach for solving this issue [15].

Security, Privacy, and Safety — The unique characteristics of smart homes enabled

by IoT, i.e., the use of distributed control, heterogeneous attack surfaces, and scale, make

it hard to provide security and privacy [74, 136]. Eavesdropping is easier as the majority

of the communication is wireless. IoT devices have low computing capability and limited

energy resources, so complex schemes cannot be implemented for enabling security [23]. End

devices belong to various organizations making the management of passwords a challenging

task. Hence, there needs to be a unified human-centered approach for solving this issue. A

2.4. Other Concerns for Smart Home Design 43

major concern regarding privacy is the uneasiness among users at being constantly watched or

listened to by smart devices. The increasingly pervasive collection of data is a serious privacy

concern as it gives away a virtual biography revealing behavioral and lifestyle patterns.

While describing an user-centric design framework for smart built environments, [48, 50]

discuss security issues, such as data integrity, confidentiality, and availability as necessary

design issues. Limited energy and computation capability of IoT devices makes it harder

to implement complex schemes as typically cryptographic algorithms require a lot of energy

and bandwidth at both ends. Wireless communication makes eavesdropping and “man-

in-the-middle attack” easier and risks data integrity as data can be modified when it tra-

verses the network, also stored data in cloud-based IoT platforms are vulnerable to security

breaches, [12]. A few light symmetric key cryptographic schemes, like Keyed-Hash Mes-

sage Authentication Code (HMAC), SMQTT and SMQTT-SN [147], have been proposed

previously, but this area still needs a lot of research [23].

Privacy, confidentiality, and trust are increasingly important in the light of privacy regu-

lations and policies [101, 137, 157] since IoT data provide insight into people behavioral

and lifestyle patterns without even the need of active participation [117]. Existing solu-

tions include employing new systems that negotiate privacy on the user’s behalf, forming a

pseudonoise while transmitting signal and adding forgetting functionalities in new software.

Safety of SBE residents must be supported by adequate IoT communication mechanisms [67].

For making rapid contextual decisions, a cloud-based system infrastructure that relies on a

strong network connection may not be sufficient [12]. In conclusion, a smart home designer

needs to be aware of the challenges and opportunities related to context awareness, safety,

security and privacy.

Energy efficiency — The demand for energy in every aspect of life is growing exponentially


with the increasingly urban world population. By 2040, about 13% of the total energy usage

would be in homes, which is a 48% rise from 2012 to 2040 [15]. The increased energy expenses

led to an increase in demand for energy efficiency. Therefore, the additional objectives of

smart homes include operational cost reduction and energy consumption reduction [15, 124].

Thus, efficient use of building systems, improving the life cycle of building utilities, etc. are

necessary criteria for smart home design. Kamilaris et al. [93] developed an energy-aware

smart home to achieve energy efficiency. Yang et al. [165] proposed a context-aware service-

based smart home energy management system which uses historical data to offer energy

usage modes like power-saving mode, general mode, etc. Even though there has been a

considerable amount of research in this area, it is still a challenge for smart home designers.

Laws and regulations — It is essential to know about the relevant laws and regulations

before embarking on the design process because smart homes collect a lot of personal data

from the users [141]. As it is a comparatively new field the regulations are still not very

concrete. Recent technologies like Fitbit, Apple Watch, etc. and Google Home kit, etc. are

able to collect sensitive data like health data, financial data, daily activity pattern, etc [15].

2.5 Conclusions

In this chapter, we have reviewed the existing literature to collate the design issues associated

with IoT based smart homes including the architectural aspect, technological aspect, chal-

lenges, and application areas. We explored the defining characteristics of SBEs compared

to traditional built environments. We also discussed the architectural design principles and

HCI techniques as useful design concepts. To the best of our knowledge, there has not been

much work on developing a comprehensive framework that addresses the holistic design pro-

cess, including architectural design and user-centered smart services design. Overall, we

2.5. Conclusions 45

identified a research gap in the existing literature and discussed the holistic smart home de-

sign process introducing architecture as an important element. We discussed the traditional

architectural design process as the baseline for a smart home design framework. We provide

a comprehensive idea about overall smart home design so that this article can effectively

work as a reference material for defining the holistic design process.

Chapter 3

Understanding the State of the Art of

Smart Home Design Process

Drawing from the experiences of subject matter experts, we mapped the current state of the

art of the smart home design process and put together different aspects of the process. We

adopted the triangulation technique [158] and conducted ethnographic studies, focus group

studies, and in-depth interviews with SMEs to identify the challenges and limitations of the

current SBE design process. Triangulation technique refers to the use of multiple methods

for understanding phenomena [132]. The purpose of this technique is to enhance the validity,

depth and explore different perspectives for understanding a qualitative research problem.

Our observations from these studies were used to incrementally develop the smart home

design framework.

We define SMEs as practitioners and researchers who have experience with smart home or

smart built environment projects. That includes architects, project managers, engineers,

construction professionals, students, and faculty of related fields. Our aim is to gather and

understand their perspectives, map their design activities/process, analyze their experiences,

and the current state of the field to get a direction for future research. We also collected

their opinions to assist in the incremental development of our proposed smart home design

framework during these studies.

46

3.1. Ethnographic Studies 47

Figure 3.1: Ethnographic study timeline.

3.1 Ethnographic Studies

We put together the best practices and guidelines for smart home design and decision-

making process and captured detailed design activities for assisting both the designer and

the occupant. To quote Benjamin Brewster,

“In theory, there is no difference between theory and practice. In practice there

is.”

Hence, we studied the practical experiences of researchers and practitioners of related fields

to understand the different aspects of smart home design. Observing designers’ activities

while they are at work is a direct approach to explore what designers do, why, and how they

do it [45].

We reported our observations from ethnographic studies on two smart home projects (Project

1, and Project 2. In the current context, the ethnographic process means immersing into

the design process of an actual smart home project. In this qualitative method, researchers

observe participants during their real-life task completion process. Authors of this disserta-

tion were involved with one of these projects and had the opportunity to observe the design

processes directly.

We associated ourselves with these two smart home projects to learn about smart homes,

design processes, challenges, and possibilities. One of them was a government housing project

48 Chapter 3. Understanding the State of the Art of Smart Home Design Process

# Partici-pantID

Discipline ProfessionalExperience

(years)

SmartEnvironment

Design Experience(years)

Current Position Focus Area

1p1

(Group 1,Project 1)

Architecture 37 30 Professor, Director, Centerfor High Performance

Environments

High Performance Buildings,Design Process, Lighting

2p2

(Group 1,Project 2)

ComputerScience

35 15 Associate Professor Smart Built Environment,Human Computer Interaction

3p3

(Group 1,Project 1)

Architecture 20 18 Director, Center for Buildingand Construction Technology

Automation in Construction

4p4

(Group 1,Project 1)

Architecture 10 3 PhD Student Design Process, Design Tools,Design Computation

5p5

(Group 1,Project 1)

Architecture 10 4 PhD Student Digital Fabrication Design,Material and Assembly

6p6

(Group 2,Project 2)

ComputerScience

16 6 Assistant Professor Smart Built Environments

7p7

(Group 2,Project 2)

ComputerScience, CivilEngineering,

Arts

8 1 PhD Student Human ComputerInteraction,

Emotion Recognition

8p8

(Group 2,Project 2)

ElectricalEngineering

3 1 Software Engineer, Research,Signature Discipline Group

Electrical Engineering (E&M)

9p9

(Group 2,Project 2)

ComputerScience

3 2 PhD Student Virtual Environments, SmartEnvironments, Tele-presence

10 p10(Group 2) Building

Construction5 2 PhD Student Human Building Interaction,

Smart Built Environment

Table 3.1: Participants’ profiles for ethnographic studies and focus group studies.

and the other was a research project of an university research lab. In this section, we

describe the two projects and include comments from the members of the design team. The

timeline of the two projects is depicted in Figure 3.1. The participants’ profiles are described

in Table 3.1.

Project 1 — As part of the ethnographic study, we shadowed the design process of Project

1 from January 2020 till August 2020 (Figure 3.1). The project was initiated in 2017 by a

government housing agency to develop a modular smart house solution which could serve the


rapidly growing housing needs. The idea is to adopt mass customization, designed based on

client needs for a standard family. The project was in the design development phase, making

decisions on the technological components and integrating those decisions with modular ar-

chitectural components when we started shadowing. We attended design meetings, observed

decision making processes, and conducted focus group studies with members of the design

team (participants p1, p3 – p5) (Table 3.1).

Project 1 provides smart technological solutions in 4 areas – HVAC, Lighting, Enclosure

(Wall, Window) and Convenience & Safety. Three design prototypes are developed for

three price ranges— Standard Level (thermostat, smart lighting), Advanced Level (smarter

lighting, communication, HVAC) and Premium Level (ambient intelligence).

The team of the Project 1 decided to provide a smart housing solution for the middle-class

through delivery and semi-automated manufacturing process. A semiautomated manufac-

turing process consists of a combination of on-site and off-site construction. Parts of the

building are built in a factory, as prefabricated modules. The other parts are constructed

on site. Finally, the modules are transported to the site and assembled together.

Participant p3 talks about their vision,

“The future of housing will have 60 percent of the manufacturing done in a

factory.”

The decision to take an off-site manufacturing approach leads to the spatial layout, material,

structure, etc. to be designed to support manufacturing in a factory following modular

conventions. Modular conventions require the design of the modules to follow some guidelines

on size, material, dimensions, weight, etc. mostly to support the transportation to the site.

Project 1 is aimed at users from a more conservative culture, so the designers did not include


Figure 3.2: Ethnographic study. Left: Project 1. Right: Project 2 [161].

any camera-based security system. p5 mentioned,

“Security cameras recording the inside of a house would not be acceptable in this

culture.”

The design team also developed a decision support system for choosing between smart tech-

nologies. Participants p1, p4, and p5 mentioned that choosing the “off-the-shelf” technology

options was the most challenging part of the whole design process. Because there is no sin-

gle technological solution available that can support the variety of basic smart technologies

needed for a home. There are numerous heterogeneous devices and a lot of them are not

compatible with each other. They propose “Choosing by Advantages” based on some criteria

and weighting to identify the most likely candidate vendors for the basic functionalities like

light, HVAC, smart home hub, etc. [64].

Project 2 — This smart house [1] was built as a research project to participate in an

international competition (Figure 3.2 : Left). Participants p1 – p2, p6 – p9, p11, p13 (Ta-

ble 3.1,Table 3.3) were involved in the project with varying capacities. Primary goal of

Project 2 was to introduce the idea of designing modular structures with integrated smart

technologies. Secondary goal was to achieve energy efficiency, ageing-in-place, and accessi-

bility. The project was first conceptualized in 2014, we observed the design process directly


from 2017 to implementation in 2018 (Figure 3.1).

The team developed their own software platform to collect data from all sensors in real-time,

aggregate, visualize, and control the smart functionalities using mobile phone and on-site

touch-screen interfaces [71]. The project team mentioned that the greatest challenge was

the absence of compatibility among heterogeneous smart devices. They built their own

system from scratch using sensors, actuators, and Raspberry Pis which is difficult to scale

for commercial use.

In Project 2, functional units like kitchen, bathroom, etc. are designed as modules which are

wired with embedded technology. These modules are prefabricated and factory produced.

They are less expensive, safer, and energy-efficient. These prefabricated, foldable cartridges

integrate technology, electrical and plumbing. These cartridges are designed by condensing

the core services of rooms like kitchen, bathroom, bedroom, and living room into modular

blocks [100].

This project also offered a solution for space constraints by providing “flex-space”, which

enables a room to adjust itself using two flank walls. These walls can move back and

forth along overhead rails to transform the same space into a home office, or a living room

based on the users’ needs and time of day. Interaction modalities include hand gestures,

touch screen, traditional switches, and MR based interaction. Touch screen displays are

embedded in the physical components of the house like walls, kitchen islands, etc. Smart

space components like LED-mounted hand gesture recognition, biometric recognition for

entry, large interactive displays incorporated with the kitchen counter, etc. are integrated

with the built environment. Project 2 offered additional functionalities like height-adjustable

fixtures, movable walls, gesture-controlled lighting, etc.

This project is designed for a specific demographic of people who need a functionality for


washing hands and feet for prayer in the washroom. Hence, the house includes a common

washroom that has a foot-washer embedded within its floor. This project had a multidis-

ciplinary design team including architects, computer scientists, electrical and mechanical

engineers, interior designers, networking technology consultants, industrial engineers, and

construction engineers.

Remarks– We came across different ideas and approaches and learned about many issues

associated with smart built environment projects. The ethnographic studies helped us de-

velop the first version of an SBE design framework which we describe in detail in Chapter 4.

We have created a word cloud to visualize the primary concerns, “pain points”, and design

approaches of the two projects in our ethnographic study (Figure 3.3). The word cloud is

a cluster of words where the size and boldness represent the importance of the topic in the

specific context. We identified the primary goals and trends of smart homes from the feed-

back: energy efficiency, convenience, controlling devices like light and HVAC, and security.

One of the most pressing challenges in the domain is the absence of a single user interface to

control the heterogeneous smart devices in a smart home. We have put together an overview

of possible technology choices for each room and which activities are enhanced by the smart

technologies for a smart home based on the studies (Table 3.2).

3.2 Focus Group Studies

In addition to the ethnographic studies, we conducted focus group studies to identify the

design processes and suggestions of subject matter experts who were team members of the

two projects. “During a focus group, a group of individuals — usually 6–12 people — is

brought together to engage in a guided discussion of a topic” [21]. Most of the semistructured

focus group discussion sessions were conducted via a video web conferencing service and

3.2. Focus Group Studies 53

Room Activity Sensor/actuator

Smart Devices

Entrance/Lobby

Circulation, Storage,Receiving packages

Occupancysensor,

Actuator,Biometricscanner

Automated door, Biometricidentification, Drone hatch

Living Room Entertainment, Socialgathering, Reconfigurable

room space

Occupancysensor,

Temperaturesensor,

Actuator fordoor/ window

Smart shade, Movablepartition wall

Home office Study, Official work,Reconfigurable room space

Occupancysensor,

Temperaturesensor,

Actuator fordoor/ window

Automated door/ window,Movable partition wall

Bedroom Relaxation, Sleep,Entertainment,

Reconfigurable room space

App-basedcontrol, Semi-automated

Smart shade, Light,Murphy bed, Mirror,Movable partition wall

Kitchen Food preparation, Socialgathering

Sensor,Actuator,

Automation

Smart monitor, SinkFaucet, Refrigerator sensor,

Oven sensor

Bathroom Personal hygiene Occupancysensors,

Touch-screenGUI, Voicecommand

Smart mirror withinteractive display, Waterrecycler, Water flow meter,Height-adjustable sink,Height-adjustable toilet

Laundryroom

Washing, Drying App-basedcontrol,

Automated

Water flow meter

Corridor Circulation Sensor Automated door/ window

Outside Relaxation, Entertainment Temperature& Humidity

sensor

Solar thermal, HVAC

Table 3.2: Example of technology choices (smart devices, sensors, actuators) for a smarthome.


Figure 3.3: Word-cloud from ethnographic studies— primary concerns, pain-points and de-sign solutions.

lasted approximately 80 minutes on average. We report our topics and observations from

these discussions– challenges, guidelines, and best practices for smart home design. We also

performed an incremental development of our proposed smart home design framework during

these focus group discussions which is described in Chapter 4.

We discussed participants’ design processes and learned about different aspects of smart

home design from their experiences (Figure 3.4 : Left).

Participants — For the focus group discussions, we recruited 10 participants who are

subject matter experts and design team members of the two projects of the ethnographic

studies. They are researchers, faculty, and practitioners who have been involved in smart

home research for decades.

Our focus group participants come from different disciplines and are experienced in differ-

ent aspects of both smart built environment design and traditional design. Participants are

faculty members, researchers, professional architects, computer scientists, project managers,

engineers, construction professionals, students, and researchers of related fields. The partici-

pants’ profiles are described in Table 3.1. There were two groups, where Group 1 consisted of

participants p1 – p5 and Group 2 consisted of participants p6 – p8. We held three meetings


Figure 3.4: Perspectives of subject matter experts. Left: Focus group discussions. Right:In-depth interviews.

with Group 1 and one meeting with Group 2. The three meetings with Group 1 were held in

person and the only meeting with Group 2 was conducted online using a video conferencing

tool.

The open-ended questions for the focus group discussions are:

1. What are the reasons for choosing the smart environment design approach? Which

technologies were chosen for your project?

2. Please describe your design and decision making process for smart home projects.

3. Please briefly discuss your view of the traditional design process and the process that

you follow as a designer.

4. Is there any existing design framework aimed at assisting smart environment design

process? Is that necessary?

5. Please discuss about the lessons learned and best practices.

6. At this point, the moderator describes the latest version of the proposed SBE design


framework to the participants and seeks their opinion and suggestions for modification.

(The responses to this question is discussed in a later chapter (Chapter 4.)

Smart Technology and Architectural Elements — From the focus group discussions,

we observed the current trends in smart home design and research, which also aligns with

our findings from the literature reviews. The primary goals are energy conservation [5, 148],

construction and maintenance safety [55, 65, 114, 159], healthcare and ageing in place [88,

100, 131], and comfort [56]. The broad typology of commonly used technologies for smart

homes are —

• Lighting— smart lights, smart switches, occupancy sensors, etc.

• Security/Safety— security camera, burglar alarms, occupancy sensors, etc.

• Thermal Comfort— smart HVAC, automated screens, window shades, etc.

• Convenience— voice assistants, robot assistants, etc.

Participants p6 - p11 were involved with the Project 2. During the focus group discussion

session, they talked about the use of flex space/reconfigurable spaces as a well-suited solution

to deal with the need for multiuse space. The pandemic has reinforced the need for such

spaces in modern homes. Moreover, the building facades/window treatments were designed

as smart components that can respond to environmental changes and can facilitate energy

efficiency along with comfort. This exemplifies the effects of smart functionality on the

architectural components of a space.

Moreover, smart functionalities also need to be designed keeping the users’ daily activities,

cultural and religious beliefs in consideration. Smart technology solutions like using cam-

eras for security solutions hamper privacy which might be completely unacceptable to some

cultures.


Design and Decision Making Process — The participants discussed the basic four

phases of a traditional design process [107].:

1. Ideation/Exploration— Requirements gathering and initial concept development.

2. Schematic Design— Initial spatial planning and technology decisions.

3. Evaluation/Development— Design development, technology infrastructure design, pro-

totype, and detail development.

4. Implementation— Bidding and construction.

The participants emphasized on the fact that each designer follows their own version of the

basic four phases. The smart technology decisions ideally come in at the Ideation phase.

Additional steps are needed to design and include the technology infrastructure within home

design. We observed that determining smart technology design goals from the beginning

allows for innovation through architectural design, delivery methods, and manufacturing

process.

Participants also mentioned,

“...there is no existing framework or defined work-flow for SBEs as this is a

relatively new field.”

A smart home project is a multidisciplinary endeavor [114]. The design team also consults

outside entities like vendor representatives. The multidisciplinary effort is needed to provide

the necessary expertise on the technology aspect as well as building construction aspects.

A decision support system can be defined by choosing vendors or technology solutions. For

example– price, availability, compatibility with other devices, functionality, etc. can be the

main determining factors.


P1 and P3 mentioned,

“In a real-life project, cost is the most important determining factor”.

Project 1 offers three levels of smartness to have three options for price range — Premium,

Advanced and Standard. Another important category to consider is addressing issues like

disability, ageing in place, etc.

Designer’s Pitch, Client Education, and Information Gathering — One of the

biggest barriers, that is, not letting a smart home to take off among occupants, is the lack

of awareness among the general population. P1 suggested,

“The design team needs to educate the occupants on what is a smart home, what

are the available smart functionalities, what are the impacts on lifestyle and

long-term energy consumption— basically what are they getting back for their

investment.”

Participant p15 mentioned,

“occupants will more readily opt for a large TV than a smart HVAC system....

till now the value proposition for a smart HVAC or automated services are not

obvious in occupants’ minds.”

For information gathering, modular conventions, sustainable design guidelines, weather and

climate data for regional climatic conditions, market research data, building codes, etc.

are necessary supporting documents. p12 mentioned that the building codes are the most

frequently used document in a smart building design.


Smart Home Maintenance/Update of Hardware/Software — Smart technologies

introduce a new problem for the occupants. Participants p7 and p8 discussed that mainte-

nance/updating hardware/software is a big issue for smart homes. This can be solved by

providing a smart home as a service where the service providers come in periodically for

software updates and hardware checks. To quote p11,

“It will be like ‘Geek Squad’ for houses.”

Smart home devices are interconnected. Therefore, safety and security issues are crucial and

need to be handled properly. For example, the Project 2 provides a completely wired system

to avoid the dangers of sniffing on wireless networks.

Smart Home in Light of the Pandemic — Our confinement during the pandemic has

taught us that better indoor-outdoor relationships in our homes and sufficient connection

with nature are important for both physical and mental well-being. Smart capabilities can

be leveraged to improve quality of life by controlling foldable window/door openings for

providing more connection to the outdoors and providing private outdoor spaces. Ambient

intelligence can also be used for responsive lighting, energy efficiency, health monitoring, and

well-being.

The need for solutions combining technological and architectural approaches depends on the

user’s unique needs. For example, an elderly person who is self-isolated at home during this

pandemic, will need support for ageing-in-place, where the home can monitor well-being,

sleep patterns, use of appliances, etc. On the other hand, a single-family home will need to

support work, entertainment, and leisure within the space.

According to the participants, reconfigurable, temporary and lightweight structures are suit-

able for supporting more activities and services like makeshift offices or study area, gyms,

play spaces, etc. Open-plan concepts along with adjustable walls/screens can be used to


# ParticipantId

Discipline ProfessionalExperience

(years)

SmartEnvironment

DesignExperience

(years)

SBEProjects


1 p4 Architecture 10 3 1 PhD Student Design Process, Design Tools,Design Computation

2 p11 ModularConstruction,Smart HomeTechnology &Architecture

25 10 9 Professor Housing, SmartEnvironments, Tele-medicine,

Disaster relief

3 p12 BuildingConstruction

17 5 1 Professor, Director of Centerfor Housing Research

Innovation in Construction

4 p13 Graphic Design 16 15 3 Assistant Professor, ProgramChair

Design Thinking, Branding,Collaboration

5 P14 BuildingConstruction

15 5 2 Assistant Professor Human-Building Interactionin High Performance

Buildings

6 p15 Architecture 7 1 1 Architectural Designer Residential Architecture

7 p16 Architecture 10 2 2 Assistant Professor Interactive Architecture

8 p17 Architecture 16 5 8 Architect Single-family Residences,Educational Institutes

9 p18 Architecture 17 0 0 Architect Residential Buildings,Program Development

10 p19 HomeAutomation

4 4 ~200 Technology Consultant Home Automation, BusinessDevelopment

Table 3.3: Participants’ profiles for individual, in-depth interviews.

transform a space into various dedicated spaces based on need. Ensuring audio-visual pri-

vacy for multiple occupants is a crucial issue to address.

Distinct transitional spaces at the entry point of a house can be conceptualized to offer

a dedicated disinfecting zone with touch-free sanitizer dispensers and a place to remove

shoes/overcoats before entering the house. More efficient air filtration systems and increased

scope for natural ventilation is also another important issue for ensuring healthy living.

Hands-free interactions for controlling utilities like– lights, faucets, HVAC, etc. are necessary

to provide more efficient functioning of the home in terms of time, energy consumption, and

reducing germ-spreading surfaces.

3.3. In-depth Interviews 61

3.3 In-depth Interviews

We conducted one-on-one discussions to gather detailed information on participants’ views

about SBE design, their design procedures, and their opinions about the current state of

the field. Their insights and perspectives offer guidance on a future direction of research in

this domain. We conducted in-depth interviews with professionals and researchers who have

previous experience with smart built environment projects (Figure 3.4 : Right). Participant

profiles for in-depth interviews are depicted in Table 3.3. We chose the participants based

on their experience in this domain and multidisciplinary background to get interdisciplinary

points of view. Participant p4 is a researcher focusing on architectural design. They were a

technology consultant and an architectural designer for Project 1. Participant p11 was the

principal investigator and research leader for Project 2 and the lumenHAUS project Fig-

ure 3.5. Participant p12 comes from a building construction background and they also have

extensive experience as a practitioner. Participant p16 is a researcher working in the domain

of interactive architecture for residential, medical, and office spaces focusing on perception-

based architecture. Participants p17, p18 are professional architects working in this domain

with decades of professional experience. They have designed houses with hi-tech features in-

stalled in them. Participant p19 is a technology consultant who provides technology solutions

to residential projects.

This individual interviews were conducted using a questionnaire-based survey (Appendix B),

either via an audio/video conference call in an interview format or through an asynchronous,

online survey option. The interviews went on for 1 hour to 1.5 hours. In the survey, we first

gathered the demographic information and then discussed participants’ experiences with

SBE design. We also discussed the incremental development of a framework aimed at SBE

design during these interviews which is described in Chapter 4. A few of the survey responses

were incomplete, so we discarded those data points. In this section, we discuss participants’


Figure 3.5: lumenHAUS [2].

opinions based on each topic.

Reasons for choosing to construct an SBE versus a TBE—

The participants emphasized on the fact that the industry is moving in the direction of smart

homes. Participant p11 mentioned,

“All houses in the near future will be smart homes, there’s just no question about

it.”

The reason for choosing to build smart buildings is to be energy positive by integrating smart

control systems. Automated control of heating/cooling can reduce energy waste (example-

Project 1). Automated insulation panel/window shutters can prevent unnecessary heat gain

during summer or heat loss during winter resulting from user negligence/error (example-

Project 1).

Participant p16 mentioned that efficient functionality and convenience, energy conservation,

healthcare, solving spatial limitations, and supporting a more mobile- lifestyle are the main

reasons for choosing the SBE approach. Participant p4 gave the reasons of efficient function-

ality, energy conversion, and comfort. Participant p12 discussed the project lumenHAUS [2],


it was a research project built to participate in an international competition (Figure 3.5).

The primary goal was to make occupant’s life simpler and more energy efficient. Partici-

pants p1 – p2, and p11 – 13 (Table 3.1,Table 3.3) were involved with this project. The design

approach of this project was to integrate architecture and technology. Participants p11 and

p12 mentioned that the main reason was to make the architecture responsive by integrating

technology for facilitating construction, transportation, and operation.

Current state of the domain and the biggest hurdles—

Participant p11 seeks to look into the smart home industry from a different perspective. Most

of the things that we use in our daily lives – automobiles, phones, TVs are all becoming smart.

However, the limitation in the built environment is that the process is so crude that there

is an inability to seamlessly integrate smart systems with it. Whereas, the industrialized

process for building a car allows for easy integration of appliances. Participant p11 said,

“We should build houses as we build cars.”

Housing is still not fully industrialized or manufactured, they are mostly constructed/assem-

bled manually on site, which is called “stick-built” or “conventionally built”. Hence, it can

not be a cutting edge from year to year.

However, the manufacturing of a house in a factory presents the possibility of seamlessly in-

tegrating technology. Hence, instead of treating the technology and architectural aspects of

smart homes as separate components, we need to consider them together and conceptualize

innovative new ways to build by utilizing industrialized methods. Adopting the prefabricat-

ing architectural approach has the potential to provide a solution to this problem. According

to participant p11,

“Modular, prefabricated components can be easily integrated with technological


components and appliances.”

For example– the main functionalities of a kitchen can be designed and built as a prefabri-

cated component. Manufactured and industrialized systems will also allow a component to

be the cutting edge state-of-the-art system from year to year. Participant p11 stated,

“Smart buildings are smart for two things – because they have integrated smart

systems and because they use smart technology to make the buildings. CNC pro-

cesses in factories streamline, economize, limit waste, and guarantee sustainable

practices.”

Issues faced by clients and designers—

While choosing homes earlier, the selection would have been between colonial style, ranch

house, etc. However, now the idea is for clients to choose the model/level of smart house

based on technology. However, the real reason for smart homes not becoming mainstream yet

is that the technology is not well integrated. For example, the Nest thermostat is supposed to

autonomously control the heating/cooling based on user’s habits. However, it is not efficient

enough yet, so users tend to move over to manual control after a while. To quote p11,

“...makes you wonder if you even need it....why do I even have a smart thermo-

stat?”

Another major problem is the difficulty of installing complex equipment in houses. Moreover,

currently the smart home technology market comprises of numerous little plug-and-play

devices with their individual apps. P11 says,

“...(we need) to develop a whole house package – energy (thermostat), building


performance, security, water usage, entertainment, car-charging, performance –

all in one user interface.”

Builders and developers can combine efforts to develop off-the-shelf, all-in-one solutions.

Individual products can provide APIs to control them. P11 suggested,

“A builder working with a tech company to build a perfect product is where the

solution lies.”

Types of smart interaction techniques that clients typically want—

The smart interaction interface that the clients want is an integrated system that includes

HVAC, entertainment, water, car, solar, affordable tech, etc. Participant p11 mentioned that

the lumenHAUS project team developed their own technology to manage its systems [68].

Many aspects of the system are controllable by the user remotely or through a smartphone.

For example, controlling the lights, temperature and monitoring local weather information,

a smart facade system, locking doors, etc. The management software also provides real-time

feedback on the energy consumption. Another comment was that multimodal interaction

techniques are not completely matured yet, for example, users do not like the awkwardness of

voice control, as it invades the privacy. The “big brother” [129] type of situations where users

are always being monitored and recorded by cameras or microphones are also something that

the users want to avoid.

Participant p4 discussed that clients typically want smart lighting, smart thermostat, and

smart security systems. As for interaction, they prefer physical switches, mobile phone

applications, and voice-based interaction.

Effects of the inclusion of smart functionality on the architectural design—


P11 argue that the inclusion of smart functionality means that the designs of homes are

going to change primarily so that they can be built in a factory.

“...so the architect in me thinks that designs are not necessarily going to change

in style but in the structural form to allow for off-site construction..... Because

if you can build components of a house like you build refrigerators, you can get

all the electronics built-in, plumbing built-in, quality of construction is perfect...”

Moreover, the materials will change (e.g., using gorilla glass) to allow the integration of

functionalities like touch screen displays, tunable LED lights, etc. In addition, the mechan-

ical controls are designed accordingly, for example, it is easier to automate a door that

slides rather than a door that swings. The smart components also need to be designed to

be accessible for repair, plug, and play portable systems. Newer functionalities are intro-

duced, for example, drone hatches to receive packages delivered by drones. The architectural

layout/floor plan is also going to change to incorporate home offices. The pandemic has ex-

pedited the scenario where a lot more people are working from home now.

Participant p4 mentioned that architectural elements are embedded with sensors and actu-

ators as a result of the inclusion of smart functionality. And reconfigurable spaces are also

impacting the architectural design.

Participants p11 and p12 stated that the smart technology inclusion changes the architectural

design. For example— the Eclipsis system [62] in the lumenHAUS project is a facade system

consisting of two sliding layers which automatically respond to environmental changes to

facilitate energy efficiency and comfort. The fully automated system allowed the house

to achieve net zero energy usage. It uses Photo-voltaic (PV) panels for carbon neutral

energy. The prefabricated construction process also reduces waste and ensures efficient and

durable production. The prefabricated, modular approach also assists in incorporating the


technology with architectural components. The spatial design is open and flowing with

height-adjustable fixtures.

Effect of SBE approach on the design process —

In some cases, the additional technologies significantly affected the architectural design.

The design process changed as the design team made design decisions along with technology

decisions. Participant p16 mentioned that the decision to construct an SBE affected the

design process by requiring additional steps for designing technology aspects and requiring

counsel from technology consultants (smart technology experts, vendor representatives, etc.).

The overall time and cost was also affected significantly.

Main challenges during the SBE design process and selecting smart technology

— One of the main challenges was finding products that could be controlled electronically

with an open API. Other big challenges include changing public opinion about smart homes

and reducing the expenses of building smart homes. Another major issue is maintenance

and updating of hardware/software, which can be solved by providing periodic services to

the clients. To quote p11,

“It’s like Geek Squad for homes.”

Participant p16 mentioned that the absence of sufficient data about available smart tech-

nology and aesthetic/psychological issues are the biggest challenges.

Main phases/steps of the SBE design process —

Participant p16 mentioned the following as the main steps during the design phase.

• Ideation

• Schematic Design


• Design Development

Participant p11 prefers integrating the system through prefabricated construction. In that

sense, the main phase is Ideation. Thinking of the house as a product like an i-Phone, the

first step is concept development and feedback. Then building a prototype and then testing

for performance before going into mass production,

“Instead of thinking of them as one-offs, think of them as a product.”

• Concept Development

• Feedback

• Prototype

• Testing

• Mass Production

Collecting requirements and feedback from clients —

Participant p11 mentioned that showing prototypes of smart homes/rooms is a great way

to gather the client’s requirements and preferences. Participant p16 collected requirements

from clients using simulations. The other participants discussed using meetings and focus

group studies as the main methods for collecting client requirements. They discussed that

getting the client’s feedback on the problems and understanding which issues need to be

solved is essential.

Effect of the ongoing COVID-19 pandemic on smart home design —

Participant p16 believes that supporting all-in-one functionality will be facilitated, creating

a paradigm shift as an aftermath of the pandemic. Participant p11 said that the pandemic

3.4. Discussion 69

will create emphasis on the need for the ability to work at home (telecommuting) and the

ability to see the doctor from home. Prefab construction will also be more advantageous as

fewer people will be involved in the manufacturing process.

Additional comments— Participant p16 observed that the existing performance metrics

for evaluating SBE design are not sufficient. Participant p11, on the other hand, said that

the energy modeling tools like Energy-Plus were really useful.

Feedback on the SBE design framework developed by the researchers. At this

point, the interviewer describes the latest version of the proposed SBE design framework to

the interviewees and seeks their opinions and suggestions for modification. (The response to

this question is discussed in a later chapter (Chapter 4.)

3.4 Discussion

The triangulation techniques consisting of ethnographic studies, focus group studies, and in-

terview sessions were helpful in realizing that the whole endeavor of smart home design is still

a scattered or loosely defined process. There needs to be a well-defined framework for the de-

sign process to properly stitch the technology and architecture components together. To that

end, we discussed participants’ design processes and learned about different aspects of smart

home design from their experiences as they have combined these two things together. We

have drawn a basic design process diagram based on the ethnographic studies (Figure 3.6).

The diagram shows the basic phases of the design process followed by the two projects –

Ideation, Schematic Design, Design Development, Evaluation, and Implementation.

The participants stated that the current practices consider the technological and architectural

aspects as separate issues. Since different disciplines like architecture, computer science, and


Figure 3.6: Design process diagram from ethnographic studies.

engineering address different aspects of smart homes, it is not considered as a holistic design

problem. Which prevents us from finding a holistic design solution. This marks the need of

elaborate research on this nascent research area where all aspects need to be combined. And

to assist the smart home design as a holistic process, there needs to be a design framework

that integrates all associated aspects. Which also includes the necessary knowledge base for

a smart home researcher and practitioner. This sort of holistic thinking can introduce novel

innovative solutions.

Researchers in the architecture and construction industry started exploring the industrializa-

tion of the smart home manufacturing process. Smart technology researchers and developers

also need to adopt a multidisciplinary approach and explore this domain by considering the

technological and architectural components together.

The ethnographic studies, focus group discussions, and in-depth interviews suggest that until

now smart technology developers and researchers have been neglecting an unified approach

that has great potential. The idea of merging the two dimensions of technology and spatial

design came up. Instead of focusing on standalone technological solutions, design thinking

needs to consider the technological and architectural aspects together and bring them under

a unified method. In our discussed ethnographic studies, architects, engineers, and construc-

tion professionals came together, and the houses were manufactured with the technological

components integrated within the architectural components–

3.4. Discussion 71

1. Project 1 conceptualized adopting modular prefabricated housing concepts. Each mod-

ule consists of main functional areas like bedroom, living room, etc.

2. Project 2 conceptualized building houses like we build cars. Each core service is thought

of as a “cartridge” and built as a component in a factory.

A noticeable observation from these examples is that combining the design concepts of differ-

ent disciplines (e.g., architecture, smart technology, industrial manufacturing, prefabrication,

modular assembly techniques, etc.) helps generate innovative ideas for smart home design.

Adopting prefabrication and semiautomated manufacturing offers a unique opportunity for

smart homes, which is – built-in technological components. This in turn has the potential

to enable mass production of cutting edge smart modules, reduce prices, limit waste, and

streamline the process.

A major issue faced by the smart home projects in our ethnographic studies was the lack of a

well-integrated technology infrastructure that can support some basic smart functionalities

for a smart home. There are too many small devices with individual apps to control them. To

address this issue, there is a need of a whole house package that controls energy (solar, elec-

tric) and HVAC (e.g., thermostat), monitors building performance (water usage, electricity),

provides security, entertainment, etc., using one single consolidated system interface.

We also learned that identifying a focus for smart technology usage and taking a user-

centered approach from the beginning of the design process helps in shaping the design

and technology choices for a smart environment project. There are a lot of moving parts

in a built environment project, the additional smart technology aspect only adds on to

the complexity. To the best of our knowledge, there is no established design framework

that integrates these pieces together and defines the design process. Hence, developing a

well-defined, user-centered framework can significantly help smart home design research and


practice.

Chapter 4

Iterative Development of a Smart

Home Design Framework

The ethnographic studies, focus group discussions, and in-depth interviews described in

Chapter 3 provide us with an understanding of the smart home design process, the current

state of the field, existing challenges, and future potentials. As it is a relatively new field,

there is no existing holistic design framework for smart homes. The only frameworks that are

available are technology frameworks, discussing solely the technology stack. However, a well-

defined and well-structured design process is essential for developing complex systems such

as smart homes [78]. We developed a holistic framework that can be used by researchers and

practitioners of smart homes. Our proposed framework, ArTSE, addresses the three primary

elements of smart homes – embedded technology, architectural elements, and occupant’s

needs.

We used the triangulation technique and applied insights from the studies described in Chap-

ter 3 and additionally conducted three rounds of Delphi studies with subject matter experts

to incrementally evaluate and develop a framework for the smart home design process (Fig-

ure 4.1). Delphi study is a structured group communication process where a group of experts

deal with an open-ended initial question and after multiple rounds of discussion, finally reach

a consensus on a result for their objective. This sort of studies are sometimes modified to

accommodate the needs of research [31, 109, 122]. We recruited participants who have ex-

73

74 Chapter 4. Iterative Development of a Smart Home Design Framework

Figure 4.1: Framework development timeline (reproduced from Figure 1.4).

perience in working with smart home projects (faculty, researchers, professional architects,

computer scientists, project managers, engineers, construction professionals, students, and

researchers of related fields). The studies were conducted via a video web conferencing

service and lasted approximately one to one and a half hours.

The ArTSE framework is aimed at single family residences and the target users are smart

home designers and researchers. This chapter describes the iterative development of this

framework. Delphi study is a semistructured group communication technique with a panel of

experts to obtain reliable opinion consensus [46]. We recruited focus group 1 as participants

for the Delphi study, because these researchers and professionals have extensive experience

with smart built environment design. Participants’ profiles are described in the Table 4.1.

The Delphi studies were conducted as open-ended discussions on the following topics —

1. Please give us your opinion about a smart built environment and a traditional archi-

tectural design process.

2. Is there any existing design framework aimed at assisting smart built environment

design process? Is that necessary?

3. Please give your feedback on the baseline framework (Figure 4.2 (Right)).

75

# Discipline ProfessionalExperience

(years)

SmartEnvironment

Design Experience(years)


p1(Group 1)

Architecture 37 30 Professor, Director, Centerfor High Performance

Environments

High Performance Buildings,Design Process, Lighting

p2(Group 1)

ComputerScience

35 15 Associate Professor Smart Built Environment,Human Computer Interaction

p3(Group 1)

Architecture 20 18 Director, Center for Buildingand Construction Technology

Automation in Construction

p4(Group 1)

Architecture 10 2 PhD Student Design Process, Design Tools,Design Computation

p5(Group 1)

Architecture 10 4 PhD Student Digital Fabrication Design,Material and Assembly

Table 4.1: Participants’ profiles for Delphi studies (reproduced from Table 3.1).

After this, the moderator describes the proposed design framework to the participants.

4. Please briefly discuss your opinion and suggestions on the proposed framework (Fig-

ure 4.3, Figure 4.6).

As a baseline for the framework, we build on our prior work (Figure 4.2 (Right)) [50] and

our insights from the studies described in Chapter 3. In a smart home, the underlying

technology framework enables the design of a context-aware physical environment [51, 153].

The physical environment design and traditional architectural concepts can facilitate design

thinking for defining the smart home design process. Interaction design for interfacing with

smart objects is another critical issue in smart home design [76]. To address all these aspects

together, this baseline describes a holistic, user-centric design framework for smart home

design [48, 50]. This is the most detailed design framework that addresses the architectural

elements, technology aspects, and user’s perspectives for smart environment design to the

best of our knowledge [50, 90].

Baseline Framework — The traditional architectural design process is depicted in Fig-

ure 4.2 (Left) and the baseline framework in Figure 4.2 (Right) [50]. The baseline framework


Figure 4.2: Left: Traditional architectural design process. Right: Baseline frameworkfor smart home design. We adopted a color code scheme for different phases where Yel-low represents Schematic Design, Blue represents Design Development, Orange representsPresentation & Evaluation, and Green represents Construction (reproduced from [50]).

divides the design process in 4 phases —

1. Schematic Design – Determining the basic scheme of the project based one user re-

quirements.

2. Design Development – Detail development of the design along with technology inte-

gration.

3. Presentation & Evaluation – Presenting the design to clients and stakeholders and

finalizing the design through an iterative process.

4. Construction – Producing working drawings and construction of the design.

We adopted a color code scheme for different phases where Yellow represents Schematic

Design, Blue represents Design Development, Orange represents Presentation & Evaluation,

and Green represents Construction (reproduced from [50]). We followed a similar scheme

throughout the document. Each of the phases are divided into steps that guide through

4.1. Developing First Iteration of the Proposed Framework 77

the smart home design process by integrating both architectural and technological concerns.

The primary difference between the traditional architectural design process and the baseline

framework is the inclusion of steps for technological concerns.

In phase 1 (schematic design), step 1.3, the baseline framework suggests using HCI models

to gather user data on technology preferences. Phase 2 (design phase) is also elaborated

further by including additional steps that are unique to smart home design —

• Step 2.2 – Technology Integration: This step consists of designing the technology

infrastructure based on the requirements defined in the first phase.

• Step 2.3 – Interaction Techniques: This step consists of designing interaction techniques

to control the smart devices and functionality.

• Step 2.4 – Data Integration: This step consists of designing the underlying data col-

lection, storage, and analysis system.

• Step 2.5 – System Architecture for Underlying Technology: This step consists of final-

izing the technology stack.

Phase 3 consists of presentation, client feedback, and evaluation. Phase 4 is for construction

which includes steps for detail development, working drawing, and construction.

4.1 Developing First Iteration of the Proposed Frame-

work

We gather feedback on the baseline framework (Figure 4.2 (Right)) during the three focus

group meetings conducted through February–April 2020 (Figure 4.1). We developed the first


iteration of our framework based on these feedbacks and by examining the process laid out

by RIBA [126], AIA [142] and literature from Lawson [107].

During the focus group discussions, participants p4 and p5 elaborated on the four phases of

design that they typically follow [107]:

1. Assimilation – Information collection about project requirements.

2. General study – Schematic design and idea generation.

3. Development – Detailed design development.

4. Communication – Conveying the design through drawings and renderings to clients

and other stakeholders.

While discussing the baseline framework, P4 suggested,

“Architecture projects are time consuming and sometimes go on for more than a

year, so it is important to be able to go back to the information collection process

from the other steps. Moreover, different levels of smartness are possible, so client

feedback is important for each step to address the specific needs of occupants.”

We conclude that the workflow of the framework should mirror the iterative nature of the

work. Participants mentioned the importance of prototype building for testing especially

in the case of smart environment. Participants discussed a challenging aspect of smart

environment design as architects,

A big hurdle for us while designing a smart home was bridging our knowledge

gap for technology design.


Figure 4.3: Iteration 1 of the proposed framework.

Smart home designers are in need of a decision support system for gathering information

about the available smart technology and choosing appropriate options considering the com-

parability between different products. Cost estimation is necessary for scoping out the

project. Participant p2 also suggested that “Phase 4” should be “Implementation” instead

of “Communication” as communication with the client is actually a continuous task through-

out the design process.

The First Iteration of the Proposed Framework— We developed the first itera-

tion (Figure 4.3) of our framework addressing the findings from the study. In the diagram,

each box represents an activity or function. The bidirectional arrows represent a two-way

relationship between the activities. The dashed arrows represent an optional relation and

the solid arrows represent a recommended relationship. We also use a “plus” (+) symbol to

mark the steps that exist in the traditional architectural process but significantly change in

SBEs, and a “star” (*) symbol to mark the steps that are unique to SBEs.

Contrary to the baseline, our workflow is iterative instead of sequential to emphasize on





the iterative nature of the work. Additionally, we emphasize more on the detailed design

activities and client feedback oriented process in phase 2 and phase 3 to better serve both

the designers and occupants. We have also structured the main phases and steps differently

to support detailed design processes. The basic idea for each phase is briefly discussed in

this section, a detailed description for each step is described in a later section along with the

final framework, ArTSE (Section 4.3).

We divided the design process into the following four phases—

1. Ideation – The first phase is dedicated to assimilating client’s requirements and other

geographic/climatic data. We suggest using HCI models to understand the client’s

activities of daily living. We also include “client feedback” as an important part of

each phase.

2. General Study – The second phase mostly consists of schematic design and making

technology decisions like which smart functionality will be provided, how does it affect

the overall spatial design, multimodal interaction techniques (voice, gesture, touch-

screen), etc.

3. Development – The third phase is where the design team develops the details of imple-

mentation. This phase consists of technology architecture and spatial infrastructure

design and testing them using prototypes.

4. Implementation – The fourth phase is dedicated to finalizing the design and drawings

and moving on to construction.


4.2 Process of Finalizing the Framework

We developed the second (Figure 4.4) and third iteration (Figure 4.5) of the framework based

on the Delphi studies. We describe the iterative development process in this section.

Developing the second and third iterations of the framework: Del-

phi Study Round 1 & 2, In-depth Interviews, Focus Group Discussions–

We modified the first iteration through two rounds of Delphi studies (Table 4.1), five in-

terviews with subject matter experts (Table 3.3), and a focus group discussion with Group

2 (Table 3.1) from May–September 2020. Throughout this process, we developed the second

and third iterations of the framework. The appendix contains the diagrams showing the

incremental development of the proposed framework (Appendix A).

Feedback and Discussion– The idea of a fully equipped smart home is gaining traction

more recently. The participants discussed that educating the occupants about available

technology options and benefits is crucial for a new concept like smart home to take off.

Participants also put much emphasis on adopting an user-centered design approach to en-

sure success. While discussing how this idea can become widely adopted, participant p12

mentioned that, in the USA more than 90% of the homes are developed by builders and they

are well positioned to offer smart homes as a service for making it widely adopted. He also

suggests,

“...this might be a more lasting effect of COVID...The shift to teleworking means

that we will see more and more automation and technology in homes.”

4.2. Process of Finalizing the Framework 83

Participants p2, p5, and p14 suggested that client feedback should be part of a continuous

feedback loop for every step in each phase. Participant p10 wondered if depending more

on the designer’s expertise and less on the client’s wishes is a better idea because they

might not always know a better solution. Participant p14 argues that with the availability

of increasingly efficient solutions like thermal enclosures and HVAC systems, the energy

efficiency of smart buildings depends more on user behavior. However, the current design

or construction practices do not follow a user-centered approach. It is a more waterfall-type

sequential approach. Participant p14 quipped,

“Current smart building construction practices are an antithesis of user-centered

design.”

The study participants validated that our work is going in the right direction and provided

suggestions for improvement. We developed the final version of the framework, ArTSE,

based on these suggestions.

Developing the final framework, ArTSE: Delphi Study Round 3–

A final round of the Delphi study with group 1 (Table 4.1) and two more interviews are

conducted from October—November 2020.

We discussed the following questions during the final round of Delphi study–

• Is it a significant contribution to the body of knowledge?

• Is it a significant advancement over what is available now?

• Was it able to capture the design process and additional requirements?


• Will you be willing to use this framework in a future smart home/environment design

project?

• Anecdotal comments.

Suggestions– We incorporated suggestions from the study participants into the final frame-

work, ArTSE. Participants p1, p10, and p11 mentioned that the maintenance/update step

needs to be considered in the last phase to emphasize on the need of sustainability of tech-

nology. Participant p1 suggested extending the framework to be one more layer deeper. This

layer (the knowledge layer) includes the tacit, explicit, and procedural knowledge about the

domain to facilitate the designer. For example, this layer discusses existing technology so-

lutions, expected input and outputs for each step, existing interaction modalities, etc. The

technological aspect is discussed in detail in Chapter 5. Participant p1 mentioned that the

inclusion of information about necessary technologies, inter-operability issues, examples, etc.,

within the framework will make it a contribution to the body of knowledge.

Participant p4 suggested developing a tool for client feedback that can assist in providing

qualitative and quantitative feedback to clients. Quantitative feedback incorporates the cost,

energy usage, etc. and qualitative feedback incorporates the information about the effect on

wellness and quality of life. Additional documentation, contractual agreements, or drawing

requirements can also be included within the steps.

Participants p1 and p4 also suggested providing a database of information to support decision

making, including links to other resources. Participant p5 commended the framework and

thanked the researchers for developing and sharing the framework. Participant p5 also

suggested showing which steps belong specifically to smart home design and which ones

were present in both smart environment and traditional architectural design.

4.3. Final Framework: Architecture and Technology in Smart Home DEsign (ArTSE) 85

Figure 4.6: Final Framework: Architecture and Technology in Smart Home DEsign(ArTSE).

4.3 Final Framework: Architecture and Technology in

Smart Home DEsign (ArTSE)

Based on the Delphi study suggestions, we elaborated the steps by including detailed design

activities (Figure 4.6). For phase 2 and phase 3, the circular layer represents two layers of

activity– the cognitive layer of making design decisions and the outer layer of communicating

with the external consultants and clients. We used the Integration Definition (IDEF) for

Function Modeling as a graphical presentation technique (Figure 4.7) [13, 135]. We discussed

the necessary inputs, outputs, controls, and mechanisms [13] while describing these activities

in detail–

• Inputs – Objects and/or data needed to perform this activity.


Figure 4.7: IDEFo’s graphical format (adapted from [13]).

• Outputs – Results or documents created by completing this activity.

• Controls – Standards, plans, templates, specifications, etc.

• Mechanisms – Necessary tools and resources to complete this activity. For example,

people with specific skillsets, specialized equipment, etc.

The computational and physical infrastructures are considered interdependent from the be-

ginning of the design process. Phases 1 and 4 are more sequential, whereas phases 2 and 3

are more iterative, consisting of two layers of activities based on the suggestions from par-

ticipant p1. Participant p13 noted that all phases do not need to be circular, for example,

we do not want to spend too much time on phase 1. Moreover, different design tasks can

be at different phases of the design process at a given time. For example, the spatial design

task can be in phase 3 at the time when the technology design task is in phase 2. For ex-

ample, at the time of the discussion, the spatial layout design task for the Project 1 was in

phase 3 (Development), whereas the technology design task was in phase 2 (General Study).

Another important suggestion from p4 is to include client agreement with client feedback so

that there is no surprise with design decisions. This is applicable for all phases.


Figure 4.8: The Ideation process.

4.3.1 Phase 1: Ideation

We layout the steps of phase 1 so that the design goals can be identified from the beginning

of the design process. A multidisciplinary team assembly leverages technology, spatial design

and building construction expertise. Client feedback loop at each step is crucial for an user-

centered design framework. The inputs, outputs, controls, and mechanisms for this phase

are–

• Inputs – Clients, program requirements, budget, etc.

• Output – Developing design requirements, concept, and cost estimates.

• Controls – Standards, plans, HCI models, etc.

• Mechanisms – Assembling a team with architects, technology consultants, computer

scientists, and engineers.

1.1 – Initial Program Analysis. The program requirements, budget, timeline and addi-

tional data– like location data, climate data, site information, etc. needs to be gathered in


Figure 4.9: Site analysis using 2D graphics (taken from [47, 48]).

the beginning (Figure 4.9). For example– to tackle the heat from dessert climate, Project 2

included a shaded porch area and vernacular vegetation in the design.

1.2 – Team Assembly. Project 1 team mentioned repeatedly that the main challenge

for them was to make the technology decisions, learn about available options, compare

between different options, etc. So team assembly with subject matter experts and seeking

advice from external consultants is an important step in smart environment design process

for ensuring success of the project. The project team can be built with architects, domain

experts, computer scientists, HCI professionals, electrical engineers, mechanical engineers,

project managers, construction managers, interior designers, etc.

1.3 – HCI Models for Info Collection. For smart home design, users’ time-based

routines, user-user/user-device relationships and psychological aspects, etc. are necessary to

understand for avoiding superficial and unnecessary technological intervention. Otherwise

the smart functionality might cause annoyance and the user might end up turning off the

functionality completely. Communication with client to understand requirements properly

is important to save effort and time. We suggest using HCI models so that the pattern


Figure 4.10: Using HCI models in smart home design [48]

language [10] is customized for each client-family by understanding user preferences [141].

The following means can be used by designers: story-telling, co-design workshops, persona,

and generating time-line of client’s activity. Well structured questionnaires can be used for

meaningful information collection (e.g., hobby, disabilities, activities of daily living, family

dynamics, etc.).

The following HCI models are useful for understanding user preferences (Figure 4.10) [48,

141]:

• Elicitation activities – Generating personas, time-line of client’s activity, spatial map

generation, etc.

• Field visits – Observing situated interaction and figuring out unexpected encounters.

• Generative Methods – Using co-design workshops to understand client’s abstract ideas

and dreams.

We conceptualized a tool following the suggestions from participants p1 and p3 to better

understand the client’s needs and vision (Figure 4.11). This is conceptualized as a “Design

your dream home”– tool where occupants can drag, drop, and design their preferred layout

and choose smart technologies based on cost estimation. These sorts of tools can greatly

reduce the timeline and expenses and provide a scope of customization in public housing


Figure 4.11: Concept sketch of a web-based “Design your dream home” tool for clients/oc-cupants for streamlining the design process.

projects. Additional useful functionality for occupants would be the ability to make a wish-

board and put together idea-images, textures, and get cost estimation based on chosen

smart devices, etc. This sort of tool helps introduce the aspects of wellbeing, aesthetics,

entertainment, and joy within the framework and overlays a wellness layer over the utilitarian

approach of solving problems. As a future work, we aim to expand this idea of self-design

functionality.

Participant p11 mentioned that showing prototypes of smart homes/rooms is a great way to

gather the client’s requirements and preferences. To quote p11,

“...a lot of the new stuff is not coming from the client. It’s coming from their

reaction to walking through smart homes, and seeing what the potential is.”

1.4 – Pitch. This step is used for developing a general concept and determining a broad

focus area based on the client’s needs. For example, the main focus could be energy con-

servation, home health care, comfort, entertainment, or a combination of these options. We

provided a comprehensive overview of the broad focus areas in Section 2.2. The overview is

aimed at informing smart home designers about the focus of existing research and practice


and to determine their design goals. In this overview, we also discussed the necessary tech-

nological approaches to achieve the SBE goals. For example, occupancy detection, remote

control of HVAC systems, etc. are effective approaches for achieving energy conservation.

Educating occupants about existing smart technologies and benefits needs to be done using

presentations and encouraging them to think at least 10 years ahead. Explaining the com-

parative long-term cost benefits and increased comfort and efficiency is necessary to facilitate

mass adoption as this is a new concept.

4.3.2 Phase 2: General Study

This phase is a circular process consisting of two layers of activity (Figure 4.12). The inner

layer is the designer’s cognitive process of making design decisions. And the outer layer is

the feedback loop with clients, consultants, or other stakeholders accessible from each step

of the inner layer. Estimating the time and cost for the client’s approval at the end of this

phase is important to avoid any surprise. The inputs, outputs, controls, and mechanisms for

this phase are–

• Inputs – Design requirements, client, etc.

• Outputs – Schematic drawings, defining technology focus and approach, cost estimates,

client agreement, etc.

• Controls – Reference plans, material selection, technology candidate choice, codes and

standards, etc.

• Mechanisms – Expert opinion from technology consultants, software developers, engi-

neers, and architects.


Figure 4.12: The General Study process.


Smart Functionalities Benefits

Controlling HVAC Energy, Comfort, Health

Controlling Security Appliances Safety, Health

Controlling Comfort Comfort, Health

Table 4.2: Capabilities and benefits of smart functionalities.

2.1 – Scheme Design. Output from the first phase is used to develop a design scheme

(Figure 4.13) based on the functional requirements and the primary focus area (e.g., energy

conservation, healthcare, etc.). The design team determines the primary focus area based on

the client’s requirements. This decision influences the overall technology choices, interaction

design, and spatial design. Table 4.2 shows how smart functionalities impact the quality of

life. Available smart home technologies can be divided into the following broad categories,

e.g.,–

• Lighting – Remotely controlling lights using voice commands, gestures, or mobile apps.

• Security/Safety – Surveillance systems, occupancy detection, wearable technology, etc.

• Thermal comfort – Remotely controlling HVAC systems using different interaction

modalities.

• Convenience – Height-adjustable fixtures, voice-assistants, assistive robots etc.

The design team can help clients make an informed decision by providing a comprehensive

overview of how each category will make an impact (Table 4.3) on the way of life. For

example, the space might respond to the user’s presence by automatically turning the light

on/off; new LED lighting systems can assist in regulating the circadian rhythm; the quality

of space can be enhanced by integrating a certain category of technology, etc.


Figure 4.13: Schematic design example. Left: Activity based layout. Right: Smart technol-ogy inclusion with spatial layout

Metrics defining quality of lifeQuantitative Qualitative

Cost Effect on activities of daily living

Maintenance/update efforts Effect on health & wellness

Operation Quality of space

Energy Use User experience

Table 4.3: Metrics for measuring the impact of each category of technology on the qualityof life– a decision support system for both the clients/occupants and design team.


The design team needs to get a green signal from the client before going into detailed

design. An overall spatial design (schematic floor plan), smart technology scheme, and

massing scheme based on activity flow diagrams and area requirements are drafted in this

step (Figure 4.13).

2.2 – Technology Decision. The broad primary focus (e.g., convenience, health technol-

ogy, security/privacy or energy efficiency, etc.) is a determining factor for making technology

decisions. We provided a comprehensive overview of the underlying technology previously

in subsection 2.2.2.

Augusto et al. defined a smart home or ambient intelligent environment as “...a digital en-

vironment that proactively but sensibly supports people in their daily lives” [24]. Smart

spaces gather data about the state of smart objects using sensors and respond to changing

conditions and user-interaction. Interconnected communication between every day objects

is necessary to facilitate such environments, which can be achieved by IoT. Therefore, the

technology system design requires successfully combining the heterogeneous sensors, actua-

tors, and devices with a software platform to develop a responsive environment and smooth

user experience.

Participants p4 and p5 mentioned that, after deciding on the technology and approach,

technology candidate choice was one of the biggest hurdles during their design process.

They explored questions like how to choose which technology, where to get appropriate

information, how to compare between available options, and what are the new expertise

needed to be taught to smart home designers. They developed and used a “choosing by

advantage” technique for choosing vendors/providers [64]. We build on this work and define

qualitative and quantitative metrics as a decision support system (Table 4.4). The metrics

can be assigned different weights based on the preference of the clients and the design team,

and the weights may change per project. For comparing the vendors/providers, the metrics


MetricsQuantitative Qualitative

Price Reliability

Capabilities UI & User Experience

Compatibility Ease of Operation

Market Penetration Cultural Adaptation

Energy Use Ease ofMaintenance/update

Table 4.4: Criteria for choosing smart technology vendor/provider– a decision support systemfor both the clients/occupants and design team.

are quantified and a final score is obtained from their weighted sum. Criteria definitions for

the decision support system are as follows–

• Price – Cost of main equipment and installation.

• Capabilities – All functionalities and capabilities, energy efficiency, etc.

• Compatibility – Ability to use the product alongside other products.

• UI & User Experience – User friendliness of the UIs.

• Cultural adaptation – Whether the product raises any cultural concern.

• Market penetration – Whether the product is readily available in the target market.

• Reliability – Whether the manufacturer can be relied on to be operational for at least

the next decade.

These metrics can be useful for suggesting technology/vendors based on the client’s criteria

and categorizing technology/vendors. If any vendor provides good enough functionality at


Figure 4.14: From left to right: (a) Gesture-based UI using Kinect to control smart lights,(b) MR-based UI, user’s POV (c) Voice command based UI, (d) GUI (OSRAM Lightifyapp). [76, 77]

a better cost, they can be chosen. For example, these comparison metrics can be used to

choose a lighting vendor from Philips Hue, Ring by Amazon, C by GE, Nanoleaf light panels,

etc.

For information collection, verification, and comparison, designers can use market research

findings, social trends, sites consisting of consumer reports, reports from sources like Stanford

Urban Informatics Lab (UIL), Chicago, and corresponding magazines in a particular area

(lighting, HVAC), etc.

2.3 – Interaction Design. There are multiple modalities for user interaction with SBEs.

Interaction modalities can be device-based (switches, GUI, input devices, etc.), where the

user monitors and controls the smart environment through a UI. On the other hand, in-

teraction can be done by utilizing the full capabilities of the human body (gesture, voice

commands, etc.), where the smart environment reacts to device-free spontaneous user ac-

tions [71, 76, 103].

Participants p8 and p13 suggested that making the interaction simple, intuitive, and acces-

sible are the primary challenges. For example– having to navigate through too many pages

in an UI for performing a simple task might frustrate users. Interfacing with a smart home

needs to be straightforward to put less cognitive burden on users [90]. Exploring an overall


acceptable level of intrusion from voice assistants/automated systems is an important part

of the design process.

We have explored how to design interactive and engaging user experiences with digital sys-

tems and SBEs through the design and implementation of interaction techniques that lever-

age multimodal embodied interactions [52, 76]. To understand the user interaction with

SBEs, we conducted a comparative study comparing four interaction modalities. Figure 4.14

depicts a comparison of four interaction modalities, i.e., Voice-based, MR-based, smart-

phone GUI-based and gesture-based interface, to compare their learnability, efficiency, and

memorability. Different interaction techniques were deemed suitable for different tasks de-

pending on the complexity and context. Our analyses suggest that a multimodal approach

is preferable to a uni-modal approach as it can leverage different techniques for different

contexts [76, 77]. Since the novel interfaces were as well received as the existing interfaces,

we suggest that future research should further explore various novel interaction techniques

to develop efficient multimodal approaches. We provide a more detailed discussion in Sec-

tion 5.2.

2.4 – Cost & Time Estimate. Budget is arguably the single most influential factor that

shapes the architectural and technology aspects of smart home design. Especially, in the

case of SBEs, there are many levels of smartness available with varying degrees of expenses.

One possible approach could be to provide an incremental standard, advanced and premium

level of smartness. The higher-end scenarios will have additional functionality, for example,

pricier Samsung fridges have monitors. A fourth category can also be conceptualized to

support elderly and differently abled people (ageing-in-place and home health care).

Even though there are multiple dimensions to technology selection, an useful functionality for

the clients would be to be able to choose different technology/ vendors based on the estimated

cost. This would help the clients to make an informed decision. Our conceptualized tool


Figure 4.15: Concept diagram of a tool for clients/occupants for vendor selection throughcost analysis.

can facilitate clients/occupants to choose products/vendors through drag and drop methods

and see the estimated cost (Figure 4.15). This can also be further extended to include other

metrics.

Phase 2 marks the design freeze for the project. It is crucial to evaluate the cost and timeline

after the schematic design and to have a client agreement. This will help avoid surprise or

denial and reduce the chances of having to go back to the design board.

4.3.3 Phase 3: Development

This phase consists of developing detailed designs based on the outcomes of phase 2. Tech-

nology decisions can affect the physical design. Some of the steps in this phase can be broken

down further to its own iterative processes. The inputs, outputs, controls, and mechanisms

for this phase are–

• Inputs – Schematic design, interaction and technology schemes, etc.

• Output – Completed drawings, technology architecture, client agreement, prototype,

etc.


Figure 4.16: The Development process.

• Controls – Standards and regulations, material selection, smart technology vendor

selection, etc.

• Mechanisms – Architects, software developers, engineers, smart technology vendors,

sales representatives, etc.

3.1 – Detailed Design. While developing the details of the design, technology decisions

may need to be integrated with physical design. For example, if reconfigurable space design

approaches are chosen in the schematic design phase, then that decision will influence the

overall spatial layout. The architectural components (e.g., walls, partitions) will need to be

designed with motors and actuators to make them movable/reconfigurable. For facilitating

home health care and adult care, height adjustable furniture and fixtures can be used along

with health monitoring sensors. The structural design, cross-section and construction process


of other architectural elements (walls, floor, and ceilings) are influenced if smart technology

is incorporated within them. In that case, the sectional designs of walls or ceilings need to

be changed to embed sensors, monitors, or devices like Kinect, etc.

3.2 – Technology Infrastructure. Technology infrastructure is one of the most crucial

factors in smart home design as this infrastructure enables the smart functionality in an

SBE. A common system that controls heating/cooling, comfort, convenience, and security

is more desirable than multiple control interfaces. A compatible, IoT-based technology

infrastructure is needed for monitoring environmental conditions, occupant’s usage pattern,

energy consumption, etc. in SBEs using sensors and smart devices. Such a system consists

of physical devices, sensors, actuators, routers, data servers, electrical wiring, and analytic

software to provide a context-aware environment. The infrastructure needs to incorporate

analysis of the collected data and make predictions based on the detected trend in support

of AmI. It also needs to provide real-time data collection, analysis, and control of devices.

We propose an IoT infrastructure consisting of three main components – data collection,

data storage, and data analysis (Figure 4.17) [153, 155].

1. Data Collection – The technology infrastructure collects contextual data using sensors

and smart devices. The data is transported to a storage archive.

2. Data Storage – Data is aggregated following a predefined structure into a data archive.

3. Data Analysis – The stored data is analyzed in real-time to find underlying usage pat-

terns and for forecasting. Providing visualization of usage data and remote/automated

control of connected devices based on the analysis enables smart capabilities.

The design and engineering team has the following options for implementing the technology

infrastructure–


Communication Protocol

ProtocolConverter

User Interface Data Extractor

Real-time Analysis

Data Archive

Sensory devices

Sensory devices

Data Collection Data Storage

Data Analysis

User

Figure 4.17: Technology infrastructure consisting of three components [153, 155].

1. Choosing “off-the-shelf” products – Choosing the available smart technology options

provided by different vendors (e.g., Amazon Alexa, Lutron lights, Kohler faucets, etc.).

2. Partnering with software providers (e.g., Alarm.com) to offer additional functionalities.

3. Developing a smart solution using existing and custom built hardware and software.

We describe our research on developing a technology infrastructure using existing and custom

built hardware and software to enable IoT-based smart homes in Section 5.1. This example

implementation can work as a baseline for developing other technological infrastructure.

3.3 – Cost Re-evaluation. Re-evaluating the cost and communicating with the client

after finalizing the design is an important step. In practice, the initial budget changes

significantly after making different design decisions and vendor choices. This is an important

step to avoid a gap in budget expectations between the client and the design team.

3.4 – Prototype, Evaluation, testing. Understanding the client’s preferences for

smart functionality using simulation/prototype is a crucial step. Participant p11 mentioned


that building example prototypes of smart space modules facilitates clients to experience

the smart functionality before making any decision. This is beneficial for ensuring client

satisfaction and avoiding unnecessary technological interventions. For example, a client

might initially like the idea of gesture-based interaction, but reject it after prototype testing.

Using novel assistive technology can also support evaluation and testing. Lertlakkhanakul

et al. [108] note, there is limited research into introducing virtual reality or web services to

the SBE design process to simulate complex, invisible smart services to end users or even

designers. They introduce a web-based virtual platform to engage end users in the design

process by allowing them to configure smart services. There has been previous research

into the use of immersive technologies for traditional architectural design as they enable

visualization and exploration of the designed space before it is constructed [30, 167]. It also

has the potential to aid in surveying a model of the site, topography, etc. without having

to be there physically [19]. Campbell et al. [34] studied and compared designs of a built

form designed with virtual reality (VR) and more traditional methods and reported the

advantages and shortcomings of VR systems.

MR devices allow for the projection of the designed space onto the real world in real scale

and allow for 3-dimensional interaction with them [19]. MR based social interaction testbed

can be used to study users’ situated interaction in an SBE [49]. Virtual twins of smart

objects can also be used to interact with the physical objects in an SBE [69].

For evaluating the performance of SBEs, designers can use simulation tools for testing energy

efficiency by daylight modeling, energy modeling, shading studies, thermal comfort, etc.


Figure 4.18: The Implementation process.

4.3.4 Phase 4: Implementation

This phase consists of wrapping up the design process and moving to implementation. The

inputs, outputs, controls, and mechanisms for this phase are–

• Inputs – Drawings, client agreement, etc.

• Output – Completed construction documents, construction, maintenance/update of

hardware/software over the life-span of the smart home, etc.

• Controls – Purchase order, deposits, building codes, etc.

• Mechanisms – Engineering teams, software developers, builders, and contractors.

4.1 – Presentation. This step represents communicating the design with stakeholders be-

fore embarking on developing working drawings and construction. Presentation can be done

using traditional techniques like graphical representation, physical models, 3D rendering,

etc.

Using novel VR/MR platforms can be another option [48]. For deciding the proper placement

of the building on site, designers and stake holders can visualize the designed building on site


in a real scale by using immersive visualization. This capability also allows them to decide

the proper placement of the building based on the surrounding context. SBE requires energy

efficiency, including data visualization in immersive technology, showing the temperature or

lighting data based on orientation, placement, depth of the building, etc. would be really

helpful. The ability to walk around in the interior and look out the window to experience the

actual view of the site is immensely helpful for the designers. Spatial mapping technology

helps placing virtual objects in the surrounding physical space. MR can also be used to

visualize different information like structural models, HVAC layout, electricity, or plumbing

layout over the built form, helping in finding out restrictions and different possible solutions.

4.2 – Working Drawing. The engineering team develops a formal architectural set of

drawings from the design drawings [13]. The set includes:

1. Architectural Drawings – Plans, sections, elevations, detail drawings, etc.

2. Drawings depicting smart devices/fixtures/furniture.

3. Structural Drawings – Structural plans, sections, elevations, joint details, etc.

4. Mechanical, electrical, plumbing (MEP) services drawings.

5. Construction documents (CD).

4.3 – Bidding, Construction. The construction process starts once the design is final-

ized. The main participants in this step are engineers, contractors, and builders. Regular

inspection by the design team throughout the construction process is important to ensure

proper implementation and quality control. Use of advanced technology can be considered.

For example, mixed reality-based systems for construction and assembly tasks and fault

detection during inspection [51].


Depending on the design, the construction process can be conducted off-site, as a modu-

lar prefabricated component or as an on-site, stick-built structure. The activities during

construction are [13]–

1. Production Drawings – Complete sets of working drawings to detail the structures and

construction of different components.

2. Structural Systems – Detailed design/drawings of structural elements of buildings.

3. Services Systems and Technology Systems – Detailed design/drawings of building ser-

vices like mechanical services, HVAC, building automation, etc.

4. Finish Systems – Detailed design/drawings of non-load bearing, exterior cladding sys-

tem.

4.4 – Maintenance/Updating. A big concern for clients/occupants is the maintenance

aspect which consists of updating/upgrading the software/hardware. There is a real concern

about technology malfunction in a highly automated system. “Smart home as a service”

can be a possible model where a service team handles maintenance/updating and software

upgrades periodically. This will help change public opinion and reluctance about smart

homes.

4.4 Reaching Consensus Through the Delphi study–

Through the final Delphi study, participants reached a consensus for finalizing the framework

and the contribution of the current work. The participants provided some additional feedback

and reached a consensus on the following points —

• This work is a significant contribution to the body of knowledge.

4.4. Reaching Consensus Through the Delphi study– 107

• This is a significant advancement over what is available now.

• It was able to capture the design process and additional requirements.

• Participants will be willing to use this framework in a future smart home/environment

design project.

Participants also provided some anecdotal comments. Participant p3 noted,

“...(the framework is) really good in capturing all the phases.”

Participant p4 stated that an SBE designer will be able to use this framework to have a clear

idea about the steps associated with an SBE project. To quote p4,

“We faced this in our project...we had to figure out everything along the way...With

your framework, we have an idea (about the process and necessary steps).”

Participants also commented that the framework serves the purpose and they will use the

framework. They also mentioned that the framework and documentation were particularly

useful for learning about the capabilities of a smart home, available technologies, how to

choose which technology, where to get appropriate information, and metrics to compare

between available options.

Overall, from our literature studies and discussions with subject matter experts (Chapter 3),

we identified the need of a well-defined design framework. Hence, we developed a holistic

design framework incorporating the three primary elements of SBEs— embedded technology,

architectural elements, and occupant’s needs. In this chapter, we have described our iterative

process using a Delphi study for developing this framework. This framework is aimed at

single family residences and the target users are smart home designers, researchers, and


practitioners. After multiple rounds of discussions, the Delphi study participants reached a

consensus about the ability of the framework in capturing the design process and additional

requirements. The study participants agreed that this framework successfully addressed the

nuances of designing a smart home. As smart home design is a complex process starting from

inception to implementation, and our developed framework provides a structured approach

to undertake this task in research and in practice.

4.5 Discussion

Our research addresses a nascent research problem at the intersection of HCI, HBI, and

architecture, where the architectural and technological aspects are brought together to start

an interdisciplinary collaboration. This nascent research problem potentially requires a new

sort of domain experts who are trained on both architectural knowledge and technological

issues. The nature of spatial usage pattern and HCI dramatically changes in SBEs. Integra-

tion of smart technology with any activity or space influences the users’ activity pattern. As

a result, it redefines the activity flow which in turn redefines the spatial layout. Moreover,

IoT has added new interaction paradigms like thing-to-thing and human-to-thing interac-

tion to the existing human-to-human interaction traditionally supported by Internet [128].

Hence, we take a holistic approach to design thinking which incorporates both technologi-

cal and architectural design aspects. We expanded the scope of design thinking to include

three primary elements of smart homes— embedded technology, architectural elements, and

occupants’ needs. We integrated the traditionally separate disciplines of architecture and

technology in the context of smart built environments design. First, we conducted an ex-

tensive literature review to understand the domain. We reviewed the design processes and

frameworks of different domains, architectural design issues, and technology aspects associ-

4.5. Discussion 109

ated with smart homes along with the challenges and use cases. We focused on exploring

the embedded technology, architectural elements and interaction modalities, and how this

codependency can be translated into existing design frameworks. We used the triangula-

tion technique in our research. We explored the opinions of subject matter experts through

ethnographic studies, focus-group studies, and in-depth interviews. Combining perspectives

from a number of related disciplines, and our observed knowledge from the studies, we have

developed a user-centered design framework for smart home design. Then we finalized the

framework by reaching consensus through Delphi studies. We also describe a case study to

develop dissemination strategies in a later chapter (Chapter 6).

Chapter 5

Technological Aspects of the ArTSE

Framework

This chapter further elaborates the technological aspects of the ArTSE framework to aug-

ment the technological decision making process. The underlying technology enables smart

capabilities in an SBE. Technology is an essential part of SBEs and we incorporated vari-

ous technological workflows in various steps of the ArTSE framework. In subsection 4.3.2,

step 2.2 (Technological Decision), the framework dictates technological decision making by

evaluating each technological choices using a set of metrics. In subsection 4.3.2, step 2.3

(Interaction Design), we discussed various available interaction techniques. One of the most

crucial factors in smart home design is technological infrastructure design which is described

in subsection 4.3.3, step 3.2 (Technological Infrastructure). Technology decision making is

a more straightforward process that can be carried out using our proposed metrics (4.4).

However, the other two steps (interaction design and technological infrastructure) require

more in-depth explanations.

This chapter provides an example implementation for the technological infrastructure step of

the ArTSE framework discussed in subsection 4.3.3– Technology Infrastructure, and explores

usability of the interaction design options discussed in subsection 4.3.2– Interaction Design.

In Section 5.1, we describe our research on developing a technology infrastructure using

existing and custom built hardware and software to enable IoT-based smart homes. This

110

5.1. A Reference Implementation of Technology Infrastructure [153, 155] 111

infrastructure is capable of storing and analyzing IoT data in smart built environments.

This example can be useful for developing other technological frameworks customized to

each project’s needs. In Section 5.2, we discuss multimodal interaction design approaches for

leveraging the enhanced capabilities of a smart space and utilizing embodied interaction. We

compared gesture-based interface, mixed-reality-based interface, and voice-based interface

with GUI-based interaction modalities. We concluded that a multimodal approach is better

than a unimodal approach as it provides the users with more options. We discuss our

research aiming to provide in-depth technological design considerations that an SBE design

team needs to know for making design and technology decisions.

5.1 A Reference Implementation of Technology Infras-

tructure [153, 155]

We describe an IoT based technology infrastructure for monitoring and controlling environ-

mental conditions and energy consumption in SBEs using low-cost sensory devices [153, 155].

This is an example implementation of the technological infrastructure step of the framework

discussed in subsection 4.3.3– Technology Infrastructure. We describe an adaptive solution

where the system collects contextual data and provides analysis and forecasting for the oc-

cupants and lets them control the devices using an interface. We have set up environmental

conditions, occupancy, and energy consumption monitoring in a laboratory space that can

be extended to an SBE scenario. The collected data were analyzed using machine learning

techniques to forecast energy consumption. Our web-based interface allows the occupants

to visualize the state of the devices and remotely manage and control them. We connect

the IoT devices using a local network. As different sensory devices may use different proto-

cols, we provide capabilities to convert different formats into a single reference format. Our

112 Chapter 5. Technological Aspects of the ArTSE Framework

web-based interface facilitates proactive decision making based on the analysis.

Several IoT infrastructures have been launched in recent years such as AWS IoT from Ama-

zon, Azure IoT Suite from Microsoft and Brillo/Weave from Google, and cloud functionality

is the backbone of such infrastructures [17]. The cloud functionality of such models might

introduce some problems for providing ambient intelligence in SBEs. The dependence on

cloud computing for analysis may increase latency. Device Shadows in AWS from Amazon

have been conceptualized, but they only store the most recent state of the device when it

was online. The device and the network do not communicate until the device becomes on-

line again. Many IoT devices depend on commercial off-the-shelf (COTS) microcontrollers

that are not deployed with hardware security compatible with these frameworks [16]. This

limits the infrastructure to use compatible devices only. Although cloud computing plays an

important role in many IoT infrastructures, network connectivity should not be a limiting

factor for an AmI environment. For that reason, we are using the OSIsoft PI system as a

non-cloud, local solution for data storage and analysis [72].

5.1.1 Challenges

IoT enables continuous sharing of data among smart devices and users, allowing monitoring

and control of devices remotely. To ensure secure communication in such a sharing environ-

ment, authentication, confidentiality, and access control are key security aspects. Therefore,

a major challenge is developing an infrastructure that has a stable, secure, and private inter-

networking mechanism. Another challenge is fast data storage, organization and analysis

to provide real-time services in SBEs. Additionally, heterogeneous IoT devices pose the

problem of dynamically integrating different types of sensory devices into the system and

organizing different types of data in a meaningful way. Another implementation challenge is


integrating periodic/real-time analysis with stored data. The infrastructure also needs to be

flexible enough to support different data analysis mechanisms. Moreover, the occupants need

to be provided with a system to remotely control the smart devices based on the analysis of

real-time data. Achieving such a holistic infrastructure is a challenging task.

5.1.2 Implementation

To overcome the discussed problems, we developed an IoT infrastructure consisting of three

main components – data collection, data storage, and data analysis (Figure 4.17).

In the case of data collection, for ensuring security and privacy, we used a wired enclosed

implementation where all devices are connected through a local network with fixed addresses.

This approach reduces the risk of network attacks like eavesdropping, sniffing, spoofing, etc.

and provides faster transmission of data.

Three types of smart sensing systems were installed in a lab setup as a proof-of-concept

implementation. These sensors allow remote monitoring and control of devices. Sensors are

connected to and powered by processing units (e.g., Raspberry Pi).

1. Environmental condition monitoring sensors to measure the pressure, temperature,

light intensity etc. of the room.

2. Energy consumption monitoring unit to measure the current consumption of a de-

vice/appliance. Thus it indicates the power consumed by the device/appliance.

3. Occupancy monitoring to detect the entry/exit of users to/from the study space.

In the case of data storage, to avoid dependency on Internet-connectivity and cloud storage

and to ensure some degree of security and privacy of the stored data, we avoided the use


of cloud services. Instead, we implemented a localized data storage and machine learning

analytic system to avoid exchanging raw data across insecure networks. The number of users

permitted to access the data were reduced to the SBE inhabitants that have access to the

local network.

Our reference implementation used Message Queue Telemetry Transport (MQTT) proto-

col [20] for communication based on the publish/subscribe paradigm. Messages are grouped

around topics, publishers broadcast messages to the MQTT broker on specific topics. Sub-

scribers subscribe to topics and receive new messages from brokers. Outside connections can

be enabled by an ssh communication between the outside network and the MQTT broker

unit, which can be used as a gateway to access other processing units.

We used OSISoft PI system (http://www.osisoft.com) as data management system to

securely store and organize time series data. This system is capable of dealing with large-

scale time-series data. Therefore, implementing different data analysis tools to receive real-

time feedback is faster and easier. We used an abstract and platform-independent messaging

format (OMF) to send payloads to the PI system. We created a linear regression model to

increase the speed of a protocol converter by adjusting the required time to empty buffer

size based on the payload traffic.

To address the issue of heterogeneous IoT devices, we implemented a model [154] capable

of organizing integrated heterogeneous sensory devices. To overcome the heterogeneity of

devices, different sensory devices are connected to a processing unit. The processing unit

acts as a bridge to provide a homogeneous mechanism by using MQTT protocol to publish

sensor data to MQTT brokers. It also acts as a bridge to provide machine-to-machine

communication (M2M), if needed.

In the case of data analysis, as a step towards building an AmI application, we implemented

http://www.osisoft.com


periodic analysis based on machine learning algorithms to process the stored data. Our

framework allows easy integration of analytical methods into the system to generate models

capable of predicting user behavior based on time series data. We provided a web interface for

the occupants to visualize the current status of devices and the results of the analyses. Time

series data can be viewed as graphs for previous hours, months, etc. The interface includes

a curated PI Vision dashboard to visualize the state of the smart devices and readings from

the sensors in real time. The interface also provides the capability of remotely controlling

the devices/appliances of the smart space. The occupants can use the interface to remotely

control the devices as a response to the visualization.

5.1.3 Case Studies

Providing support for AmI environment requires a stable infrastructure that provides sen-

sitivity and responsiveness, and is context-aware to provide intelligence and adeptness. We

described three case studies to explore the various functionalities of the proposed infras-

tructure. The purposes of these case studies are to check the stability of the system over

a long duration of time and explore machine learning approaches towards creating an AmI

environment.

Case Study 1: Exploring System Stability

A dedicated room used for case studies and experiments was prepared to continuously gener-

ate heterogeneous data over the period of 20 days for the first set of sensory devices and five

days for the second set. We divided the sensory devices into two categories: environment

monitoring units and energy consumption units

The sensory units used for monitoring the study space are as follows:


Processing Unit

MQTTPublisher

MQTTBroker

Processing Unit UFL connectorfor historical data

Restful Web Application

Extract Using AF SDK

Real-time Analysis

PI System

MQTTSubscriber

MQTT to OMF

Storin

g analysis resu

lts

Photo resistor

Barometer

360 Lidar

Unidirectional Lidar

Thermistor

Current Monitoring

Data Collection Data Storage

Data Analysis

Data Collection setup

Figure 5.1: Study setup.

• One barometer for measuring the pressure, temperature, and altitude of the room

@1Hz

• One thermistor to measure room temperature with higher accuracy @2Hz

• One photo resistor to measure the intensity of the light inside the room @2Hz

• One Unidirectional Lidar for detecting a person entering the room @10Hz

As an energy consumption unit, a current monitoring controller was used to monitor four

devices, two server desktops, and two monitors, over a period of five days.

In this implementation, we are using two Raspberry Pis, as our processing unit to convert het-

erogeneous sensory data into homogeneous data using MQTT protocol. Another Raspberry

Pi is used as a MQTT broker. Figure 5.1 shows a diagram of the implemented setup.

The PI server subscribes to the topics, converts MQTT to OMF messages, and stores the

data into the database. There are two options to monitor a data. The user interface uses the


RESTful approach to provide a web-based user interface. Figure 5.2 (Left) shows the graph

depicting real-time temperature, light, and energy consumption data. From the graphs, it

is easy to understand the usage pattern and the correlation between different parameters.

We developed a web-based user interface that includes a customized dashboard for each

room. Occupants are able to observe periodic updates in time series data for monitoring

the smart space. Based on the observation, they can click on buttons that publish MQTT

messages to the broker, the smart devices subscribe to the relevant topics and receive the

commands. Thus, the state of the smart devices can be changed using this approach (Figure

5.2 (Right)). Users can gain access to the web interface by using any browser on the local

network using the network address.

During the 20 days of recording the data, no failure in the system was detected. No packet

loss was detected, as we used QoS 1 and wired local networking. Although, some latency

between receiving the message might have occurred. The process of retrieving 1 million

points from the database requires around 9 seconds of processing time (µ = 9.33, σ = 0.4).

The size of the data stored in the database is around 60 MB per day (µ = 60.5, σ = 3.5).

Case Study 2: Device Recognition

For implementing an AmI environment, we aim to accomplish two main tasks. First, the

environment needs to be able to recognize the different devices that are available inside the

room. Second, the environment needs to learn the patterns that might occur in different

devices and be able to predict and broadcast them. In this case study, we explored how the

system can recognize the devices.

To test our model, we fed “ACS-F2” dataset [139] into the system. The database provides

consumption device signatures over the duration of one hour. The data contains 255 home


Figure 5.2: Left: User interface showing time-series data depicting temperature, light, en-ergy consumption. Right: Web interface with MQTT publisher for controlling differentdevices based on real-time data.

Figure 5.3: Left: The Confusion Matrix generated by using seven minutes of the simulatedenergy consumption signatures. Right: The Confusion Matrix generated using 15 minutesof the data.

appliances divided into 15 categories. The model retrieves the data from the simulated ap-

pliance. By using simple k-nearest neighbor classification, the system is capable of detecting

the category of the device. The results from our study show that as little as seven minutes of

appliance consumption can be sufficient to determine the appliance category with acceptable

accuracy [154]. Figure 5.3 depicts the confusion matrix for seven minutes and 15 minutes


Figure 5.4: The predicted value in blue compared to real value in orange. Top Left and TopRight: Examples of true positive. Bottom Left: An example of false negative. BottomRight: An example of false positive.

of appliance energy consumption generated by the simulation. As the result shows, more

energy consumption data will enable the model to recognize the device with higher accuracy.

Case Study 3: Predicting Energy Consumption

The goal of this case study was to provide a periodic analytic system that broadcasts the

results. A periodic forecasting method was implemented to analyze the energy consumption

of solar panels. We monitored the solar panels over a period of 19 days. During this time, a

forecasting program was scheduled at 4 PM to forecast the next 14 hours, using the stored

time series data of a battery voltage as a training set. After processing, the forecast model

uses Simple Mail Transfer Protocol (SMTP) to notify users, at what time the value becomes

less than 52 Volts.

15 predictions were reported during this time. We compared the predicted values with the


actual values. If the reported time was in the range of the real value within a delta time of

30 minutes, we considered the report as true positive. We excluded the first two days from

our analysis, due to the insufficient training data. Overall, nine true positives, one false

positive, and three false negatives were reported during this study. Figure 5.4 shows some

of the results comparing predictions to the real values.

5.1.4 Discussion

In this section, we describe a multipurpose, flexible IoT-based technology infrastructure for

SBE monitoring and control systems in support of AmI. The infrastructure provides a simple

way to implement different machine learning applications that can be used to analyze the

stored data. Three case studies were used to explore the stability and potential of machine

learning approaches using the SBE sensor data. The results of the first case study show that

the system is stable and it can collect data over a long period of time without failure. The

process of retrieving one million data points of stored data requires around nine seconds.

This makes the infrastructure capable of providing a periodic analysis on the data that can

be used for training purposes.

The infrastructure provides an intuitive way to add multiple analytical methods to process

the recorded data. In the second case study, the system was capable of predicting the

category of simulated appliances based on their energy consumption signature using “ACS-

F2” database [139]. This approach can be used inside the system to recognize different

sensory units inside the building.

Finally, in our third case study, we explored how a forecasting method can be used to predict

the outcomes based on the recorded data. The proposed infrastructure supports features

such as sensitivity, adaptability, and intelligence that are required for AmI environment for

5.2. Interaction Design: A Discussion on Four Interaction Modalities [76] 121

SBEs. Our reference implementation can be an example for developing smart technological

solutions.

5.2 Interaction Design: A Discussion on Four Interac-

tion Modalities [76]

This section explores the interaction design options in the context of our proposed framework,

ArTSE, as discussed in subsection 4.3.2– Interaction Design. With the increase in the number

of connected devices in SBEs, the level of complexity involved in interacting with these

environments increases significantly [77]. Traditional HCI techniques are not always well-

suited for SBEs and this poses some unique usability challenges. To facilitate interactions

within such technology-rich SBEs, new models and interaction interfaces need to be explored.

In a previous research, we proposed a multimodal approach for interacting with smart en-

vironments [76]. We also conducted a user study to compare the learnability, efficiency,

and memorability of four interfaces: voice-based interfaces, GUI-based, gesture-based, and

MR-based interface. Our user study experiment involved four light control tasks that sub-

jects were asked to complete using four interaction interfaces. Study subjects found different

interaction techniques to be more suitable for different tasks based on the type, complex-

ity, and context of the task. We explored the usability, learnability, and memorability of

each modality, to identify both their scope and their limitations. Learnability was tested by

observing the initial performance of users while interacting with the four UIs for the first

time. Memorability was tested by evaluating subject task performance between two study

sessions. And finally, usability was measured through a combination of qualitative feedback

analysis and evaluation of task completion time. Our analysis of the study results and sub-


ject feedback suggested that a multimodal approach is preferable to a unimodal approach

for interacting with SBEs.

In this section, we discuss common and novel interaction techniques, their strengths, and

weaknesses. We suggest that novel interaction techniques need to be further explored to

develop efficient multimodal approaches along with the widely used techniques [76, 77].

Discussion

The burgeoning number of embedded smart devices poses a challenge to interaction de-

sign [110]. An SBE is capable of understanding user input through touch, voice, gesture,

thoughts, etc. An SBE is also able to provide output using graphical, audio, or MR user

interfaces. Interaction modalities can be device-based (switches, input devices, etc.), where

the user monitors and controls the smart environment through a UI. On the other hand,

interaction can be done by utilizing the capabilities of the human body (gesture, voice com-

mands, etc.), where the smart environment reacts to device-free spontaneous user actions.

Commonly used interaction techniques were developed in the world of desktop computers.

Therefore, they do not leverage the full capabilities of smart environments or the human

body.

SBEs can gather and apply contextual information in aiding users with autonomous ac-

tion [138]. However, autonomous action may prove to be inefficient and over-patronizing for

users. Users require a simple and convenient user interface (UI) for conducting their day-

to-day activities in a smart environment [103, 140]. Home environment interfaces can be

either simple distributed interfaces or can comprise of more complex interfaces [105]. Light

switches are an example of simple interfaces while TV and A/V controllers are examples

of complex interfaces. These diverse interaction scenarios in SBEs are more intricate and


complicated because of the sheer volume of functionality and interaction opportunities that

they provide, thereby demanding that additional research be conducted in this area [40, 103].

Nowadays, Graphical User Interfaces, leveraging the ubiquity of smartphones are dominant

in supporting user interaction with smart devices [103, 140]. GUIs provide a readily available

user interface as smartphones have become a part and parcel of our daily lives. GUI is more

useful for relatively complex tasks and for remotely controlling devices when the user is

not in the same physical space. However, complicated UI design can significantly increase

the task completion time even for an widely used interaction technique like GUI. Increasing

number of smart things makes it difficult for users to maintain a mental mapping of things

to apps. Having to switch between apps for different devices complicates user experience

and increases cognitive workload.

Mapping a 3D physical space to a two-dimensional (2D) layout displayed on a smartphone

screen can be tricky and may confuse users. For instance, turning a light switch on/off in

a home environment using a smartphone GUI might be seen as excessive and impractical

compared to simply using a physical light switch. One interesting functionality for future

researchers to develop would be to point the smartphone towards a smart device resulting in

the relevant app page opening up in the GUI. Including a layout plan of the built environment

within the GUI and placing device icons in the corresponding locations could also be helpful

for mapping the UI to the physical device.

Voice-based UI is gaining popularity in recent times, especially for smart home scenarios

because it resembles natural human communication. Voice-based interaction is intuitive, es-

pecially for simple tasks like controlling lights, air conditioning, etc. However, more complex

systems with various parameters pose a problem for voice-based interaction (e.g., controlling

the color and brightness of tens of light sources). Sometimes the verbal commands to inter-

act with a smart object can be too long-winded, causing users to forget these commands.


Whereas, a GUI or hand gesture-based interface could prove to be faster and much simpler

for that task. In such a scenario, users would prefer using other UIs. Voice-based UI also

needs to accommodate the issues faced by non-native speakers. For example, making the

commands simpler and shorter, allowing for prolonged pauses or filler words.

Similarly, although voice-based UIs can provide a more natural way of interaction, mapping

smart devices to a set of pronounced names may not scale well with the rapidly increasing

number of devices in a smart environment. Memorizing voice commands and device names

can also introduce a considerable mental workload. Current practices of interaction design

in SBEs do not leverage the full capabilities of the human body. There is, therefore, a need

for more intuitive, seamless, and efficient interaction interfaces for SBEs [103].

The gesture-based UI is a hands-free option which frees the user from having to carry a

controller. Our study subjects were intrigued by the intuitiveness of this interface. However,

along the same lines with the findings of Kuhnel et al. [105], we conclude that gesture is more

suitable for straightforward and common interactions that have intuitive gestural perceptions

among users. For example, physically inspired gestures like “Up” and “Down” for “On” and

“Off”. The success of a gesture-based system has high dependence on the intuitiveness of

the gestures and user familiarity with the rotation direction of other interfaces like light/fan

regulators or switch on/off direction. Cultural factors (e.g., writing direction) also effect the

user’s intuition. Gesture-based interaction is more suitable for scenarios where the user and

the device are both in the same physical location.

Gesture-based interaction can provide for embodied and instantaneous interaction that lever-

ages the capabilities of the human body. In doing so, gesture-based interaction can allow

users to simply point at smart objects to control them and spare them the burden of having

to remember a plethora of complicated device names. Petersen et al. [134] evaluated the po-

tential of using gestures in their user study and determined that 80% of their study subjects


preferred to use a gestural interface over more traditional interfaces like GUIs.

MR can be a potentially useful input modality because a smart environment is likely to have

numerous, potentially undetectable smart devices and it can be quite difficult to identify

and leverage their smart capabilities to full potential through traditional control interfaces.

The enhanced capability of MR devices can assist users in detecting and interfacing with

various smart functionalities.

A 3D digital medium like MR provides a greater amount of visual and contextual infor-

mation using holograms, lending it to be better suited for interfacing with a large number

of distributed smart objects, which would be otherwise difficult to control using traditional

interfaces. The holographic projection on top of the real environment is useful for com-

plex tasks like maintenance and assembly. Virtual indicators might be useful for indicating

proper placement of parts in case of assembly [42]. Contrarily, using a heavy, head-mounted

device at home for a simple light control task might be redundant. Even though the re-

cent MR devices are fairly light, users prefer even lighter options in the case of a wearable

device for day-to-day use in a smart home context. Other SBEs like smart factory, smart

warehouse, smart industry, etc. could be more suitable for MR-based interaction. The most

frequently used interactions need their separate buttons, gestures, or commands which are

easy to memorize or placed in a focal point of the GUI.

Overall, our findings suggest that different modalities were more suitable for different types

of tasks. SBEs consist of objects that are imbued with computation and communication

capabilities. This opens up numerous novel interaction possibilities that leverage recent

technological advances, like MR and embodied interaction. Different modes of interaction

have different strengths and weaknesses based on the task type. Hence, a multimodal ap-

proach combining novel and traditional techniques provides users with more flexible and

varied interaction options.

Chapter 6

Dissemination

In this chapter, we explore the application of the ArTSE framework using a case study to de-

velop dissemination strategies. We also aim to identify potential issues with implementation

through the case study. The case study is a research project for designing a smart recon-

figurable space (SReS) for a common area in a residential hall at Virginia Tech. The aim

is to ensure that the space is empathetic/responsive to the users’ needs. We introduced the

ArTSE framework to the project team using a manuscript and PowerPoint presentations.

The design team followed the framework throughout their design process and reported the

issues that they have faced while going through the steps. They have also published a part

of their research and discussed the use of the framework [59].

We will first discuss the limitations of our case study. A limiting factor is that the study

participants were already familiar with our research, which could have potentially biased

their feedback. The study participants are researchers working in the domain of smart

reconfigurable spaces and they come from a building construction and computer science

background which meets part of our requirements. Future research directions can include

conducting case studies with architects and builders as they are the primary target audience

of the framework. Limitations of the research also include a lack of testing outside of smart

home design. Expanding the current research to include other use cases like smart offices,

schools, etc. could open up possibilities for extending the ArTSE framework to support

other types of SBEs.

126

6.1. Case Study: The SReS Project 127

The SReS project is a suitable case study for us as our framework is aimed at residential

projects and this SBE design project is focused on designing a common area for a residential

hall. The goal of this project is to improve the efficiency of indoor space utilization by

creating an optimum layout for each activity and maximizing occupancy. As the pandemic

has put in a lot of restrictions on space utilization, this research addresses a timely concern.

This project could benefit from combining architectural and technological considerations as

it is mostly concerned about space and its maximal utilization. Since this project deals

with reconfiguring and redefining the space, architecture will play a vital role in this. This

project also needs assistance from smart technologies for physically reshaping the space,

so technological concerns are also crucial. Our framework aims to bring architectural and

technological design aspects together to offer a holistic design process for SBEs. Hence, the

project team utilized our framework during their design process.

6.1 Case Study: The SReS Project

The reconfigurable space design project was used for exploring the implementation strategies

of our framework. In this section, we describe our findings from this case study. We also

include the design team’s feedback and comments about the usability of the framework. This

preliminary application helped us in developing instruments for implementing the framework.

The Corps of Cadets at Virginia Tech are the clients of this project. The project entails

designing a common area cum lounge in one of the cadet residence halls at Virginia Tech [59].

The initial idea behind the project was that the space will reconfigure itself based on the

time of the day and usage so that it can maximize the spatial distance between seating ar-

rangements to minimize the spread of infection. In the beginning, the idea was to reconfigure

almost all components of the room, e.g., the walls and furniture. Later, the project scope

128 Chapter 6. Dissemination

was narrowed down to re-configuring the room layout and the furniture themselves. The

final outcome included creation of a layout for maximum occupancy and developing various

reconfiguration strategies.

Initially, the design team intended to follow a generic HCI design approach or activity flow.

Where the first step is to get the user requirement, then design development, building a

prototype, getting user feedback on that prototype, and then finalizing the last product.

After getting introduced to our framework, they started using the framework throughout

the design process.

We held an initial one-hour meeting (September 2020) to introduce the ArTSE framework

to the team. We have provided the framework along with the detailed descriptions as a

manuscript (Section 4.3). We have also presented the framework using presentation slides.

After that, they used our framework throughout the smart reconfigurable space design pro-

cess. We conducted a 40 minute interview (January 2021) to learn about their experiences

throughout the process.

Open ended questions for discussion:

1. Please give a brief introduction of your smart environment project.

2. What were the reasons for choosing the smart environment design approach for your

project?

3. Please provide your feedback on using the SBE framework throughout the design and

decision making process for your smart environment project.

4. What were the reasons for choosing this framework?

5. Is there any other existing design framework aimed at assisting smart environment

design process?


6. What do you expect from such a framework?

7. Please discuss the lessons learned and best practices.

6.1.1 Qualitative Feedback

After getting introduced to the framework, the design team mentioned that the framework

provided them a structured way of looking at the design process. As this was a research

project, some of the steps mentioned in the SBE framework were not applicable for them,

e.g., implementation, detailed drawings, etc. The team mapped their design process using

the framework and discussed what was useful or if anything was missing. They mentioned

that,

“The steps of the framework perfectly align with the necessary actions (for de-

signing a smart space).”

The first part, Ideation Phase (phase 1), consisted of coming up with ideas, collecting in-

formation through multiple interviews and meetings, and determining users for the example

implementation. The cadets have a social lounge (about 380 sqft) that they use either for

study or for company meetings. These two main configurations require different space usage.

Therefore, during the Ideation phase, the design team conceptualized changing the layout of

the room automatically to accommodate whatever activity they are doing.

The team mentioned that the SBE framework helped them realize the importance of com-

municating thoroughly with the clients,

“...the “Pitch” step is actually an important step for smart environment design

projects.”


The project team had to convince the clients that there will not be “too much reconfigura-

tion” happening in that space. Some of the students were excited about the novel concept.

In the General Study Phase (phase 2), the inner layer of the cognitive process consisted of

using generative design approaches [59] for creating schematic layouts of the reconfigurable

spaces. The technology decision step consists of choosing interaction techniques for informing

users about moving objects in the space. The outer layer of the feedback loop consisted of

interviews with clients and consulting their advisor. The cost and time estimate step was

not applicable for them.

For the Development Phase (phase 3), the project team is working on two options— first

one is creating layouts with existing furniture and the second one is proposing new foldable,

reconfigurable furniture. As there will not be any prototype building, the team decided to

use virtual reality for testing the usability of the reconfigurable space by conducting a user

study.

The Implementation Phase (phase 4) is not applicable for them. To quote them,

“..but at least these first three phases of the framework we did include in the

study.”

Experience and feedback— When asked if they found the framework useful, one of the

team members responded,

“I think it was very useful, in the sense that it helped us realize a lot of things

that we were missing earlier. When we started, we had a very vague idea on

how and what we should do to come up with a solution. But, as we looked at the

framework...it helped us find all those missing pieces and put them in place....and

we are still learning as we look at it. And we will probably learn more as the


project progresses. ”

For example, the team have not discussed the implementation techniques for automation

yet, but looking at the framework they realize that they need to figure out the most efficient

implementation too.

One other aspect of the framework that the users liked was,

“for any project in real life, the most important constraint that comes for im-

plementing such projects is the time and the cost constraint. And I think this

framework also captures that.”

When asked if they have looked for any framework at the beginning of the design process,

the users mentioned that they were mostly relying on their and their research advisor’s

experience. When asked if they knew of any such existing framework that focuses on smart

environment design, one of the users mentioned,

“...having worked in the area of built environments and smart built environments,

for a good amount of time, I have not come across any framework that suggests

the design and development of smart built environments....In our case, we mostly

follow our prior experiences with HCI, and UI/UX design, for the design process.

But, if we had this framework to start with, then probably our design process would

have been a lot better. Nevertheless, this framework was introduced to us. And

at whatever time it was introduced to us, it did help us a lot in kind of filling up

those missing pieces and those gaps in the current project.”

We discussed the currently available guidelines for traditional built environments. One of

the participants worked in the Indian real estate development industry and he mentioned


that the process guidelines that they followed were mostly a set of rules and procedures—

building codes, standard dimensions, and rules of thumb related to ergonomics. There was

no framework comparable to this. The user also mentioned,

“these rules or guidelines were not human centered...there was very little human

involvement in the design process. For example, if you have to design a room of

a certain size, then you would need to follow certain standard dimensions and

building codes, and then the room will be appropriate for a certain number of

people... and just follow this rule and design the room. And that’s it.”

We also discussed about the additional aspect of smart homes, the integration of technology,

and if the framework was able to capture that. The users mentioned that as they were

not planning to implement the project, rather simulate the smart capabilities using virtual

reality, they did not duel too much on the actual technologies to use.

“But if I think about implementing, then the selection of technology and the sus-

tainability of technology becomes very important.....because that would drastically

affect the budget, maintenance, and ease of implementation of the project....it

affects a lot of factors that are listed in the framework. ”

While discussing how the smart capabilities have impacted the design process, the users

mentioned that the decision to pursue a smart design approach has fundamentally changed

the whole design process. Increased use of technology as design tools significantly increased

because of the smart design approach. The use of generative design to figure out an optimal

layout was also adopted because of the smart environment design. Convincing the clients was

also more difficult, because people are still apprehensive of the extensive use of technology

within the built environment. We discussed about the next steps when the users start


thinking about the implementation of the project. Taking guidance from the framework,

they discussed that for real world objects to move around, there would be a need for sensors

and actuators that are also context-aware to alert people when things are moving.

6.1.2 Quantitative Feedback Using SUS Score

The System Usability Scale (SUS) [32], created by John Brooke in 1986, is a “quick and

dirty” usability scale consisting of 10 questions for evaluating a system. The calculated SUS

score from the users’ feedback is 90 out of a possible score of 100. This score gives us an

idea about the usability of our framework. We report the users’ responses and feedback in

this section.

The scale we are using here is as follows:

1. Strongly Disagree 2. Somewhat Disagree 3. Neutral 4. Somewhat Agree 5. Strongly

Agree

1. I think that I would like to use this framework frequently.

Response & Feedback: 5

“Yes, I would like to use the framework more often. It definitely helped us put

some of the missing pieces together and gave us a direction to go forward.”

2. I found the framework unnecessarily complex.



“The framework appeared complex on the first look but as we started imple-

menting it became easier to understand.”

3. I thought the framework was easy to use.


“The framework was a bit complex at first, but it became easier to understand

as we started working with it.”

4. I think that I would need the support of a technical person to be able to use this

framework.


“I will not need technical support to implement the framework, but I might

need some assistance in making technology decisions.”

5. I found the various functions in this framework were well integrated.


“I do believe that various functions in this framework were well integrated.

I really like the fact that the framework has some client involvement in all

the phases.”

6. I thought there was too much inconsistency in this framework.



“I do not think there were inconsistencies in the framework. The client

feedback can seem repetitive but I think it is important have some client

involvement in all the phases.”

7. I would imagine that most people would learn to use this framework very quickly.


“It can become overwhelming for first time users to understand the frame-

work.”

8. I found the framework very cumbersome to use.


“I did not find the framework cumbersome to use. My past experience made

it easy for me to implement this framework.”

9. I felt very confident using the framework.


“My experience with building design and UX/UI design made it easier for

me to implement the framework.”

10. I needed to learn a lot of things before I could get going with this framework.


“I do need to learn more about technology implementation but I was still able

to use most of the framework in my project.”


6.1.3 Suggestions From the Case-study Participants Regarding

the Framework

Case study participants provided feedback based on their experience in designing SBEs and

their expectations from the design framework. Participants mentioned that the learning

curve is the biggest hurdle while using any technology; this framework provides a compre-

hensive overview which helps in the learning process. Participants also suggested that a

type of inventory/database to know about the available options for the technology stack

would be useful. Limited and scattered data sources and lack of a comparative matrix is

a problem. Having access to suggestions for choosing sensors or communication protocols

or presentation techniques would be useful. They also requested us to include a detailed

description for each step which explains what activities actually go into it.

The participants also mentioned that too much client feedback might hinder the design

process. A design freeze is necessary at some point. The maintenance/update step can be

added in the last phase to emphasize the need of sustainability of technology.

The users also had some suggestions about future work,

“...this is a very good framework for design. But you can probably also generate a

framework for implementation. Like, you can probably map out all the capabilities

that a smart house can have. And then list the technologies that are available.....I

think the biggest challenge with smart technologies is that every device is working

on its own platform...probably the implementation phase can suggest an ecosystem

of devices, which can work together with each other without any changes in

programming, or technology, probably that would help”

We have addressed the feedback and included the requested additional information within

6.2. Dissemination Guidelines 137

our framework.

6.2 Dissemination Guidelines

We have considered a number of ways for disseminating the framework and sharing our

research findings to target users, stakeholders, and domain experts. It is necessary to make

sure that the research outcome is adopted and widely used by the target users.

• The purpose is to inform, promote, and educate the target audience about our research

outcomes and the ArTSE framework.

• The content is the description of the framework and other resource materials docu-

mented in this dissertation.

• Target users are smart home designers, researchers, and practitioners.

• The first step would be packaging the framework as a booklet and a recorded presenta-

tion. The booklet will contain a detailed description of each step of the framework and

emphasize on the unique SBE-specific aspects (Section 4.3). For example, as it is an

SBE, we need to produce additional working drawings depicting smart technology and

list the choices such as gesture, voice, etc., to be used in the interaction design. The

descriptions will also point out the changes in the global organization of the processes

and the specific changes in each step because of it being SBE and not a traditional

architectural process. Later on, workshops and seminars with smart home researchers,

designers, and architects can be a way to ensure that the framework ends up in the

hands of smart home designers.

Chapter 7

Conclusion

The housing industry is moving fast towards adopting smart home technologies. As smart

homes consist of smart objects with computational and communication capabilities, they

are different from the traditional built environments. The ongoing COVID-19 pandemic has

resulted in an increased reliance on our homes. As a result, future homes will tend to be

more adaptable for supporting a more comprehensive array of activities/services, and smart

homes can provide the necessary capabilities for that. Hence, it is about time to explore

the domain from an interdisciplinary perspective and define the processes that go into smart

home design. As a relatively new field, the SBE/smart home design process does not have any

well-defined framework yet that addresses the technological aspects, architectural elements,

and user’s needs. However, a guiding structure is necessary for any complex process, as it

provides reliability, consistency, and scaffolding for a project. Taking a holistic approach to

the design process can open up pathways to innovation towards reimagining smart homes.

In this dissertation, we explore both the technology aspects and the architectural design is-

sues associated with IoT based smart homes. From a comprehensive literature review of the

issues and concepts related to smart home design, we have identified that there is a need for

more research in the area of smart homes at the intersection of architectural design-thinking

and smart technology-based design process involving HCI, IoT, and HBI. Collaboration be-

tween the two domains of HCI and architecture is a timely subject entailing the construction

138

139

of a framework that can be compatible both with design research and architectural processes.

In that sense, this dissertation contributes to a novel trend of research work that seeks to

create situations of concrete project-based collaboration between the practitioners of the two

fields.

We developed a smart home design framework ArTSE, by drawing expertise from various

domains concerning design processes. We envisioned this framework as a guiding structure

for smart home projects by bringing architectural and technological design aspects together.

We propose an integrated design process that acknowledges the interplay among the embed-

ded technology aspects, architectural elements, and occupant’s needs within the framework.

Our framework supports aspects of wellbeing, aesthetics, entertainment, and joy by incor-

porating an active participation of the occupants/clients within the design process. Our

research produces a theoretical contribution influenced by the normative theory in archi-

tectural design. “A normative theory of architecture is a set of normative rules about how

buildings should be done rather than how buildings are” [81]. It is the position of architects

that explains what good architecture is and how the practice needs to be conducted [106].

Our developed framework is an evolution of the normative theory design process that caters

to the needs of smart homes.

A limiting factor of our work is the lack of exploration outside smart home design. While

developing the framework, we have conducted ethnographic studies on residential projects

(single-family residences). The subject matter experts that we have consulted during the

focus group studies, interviews, and Delphi studies, are also mostly focused on the residential

sector. The case study for developing dissemination strategies is also a residential project.

Hence, our framework is primarily aimed at residential projects, particularly at single family

residences. Other residential use cases like residential halls, multifamily residences, etc., can

also be covered by this framework. During the development process of the framework, we

140 Chapter 7. Conclusion

did not focus on other use cases, i.e., office buildings, educational institutes, retail property,

factories, etc. However, this framework can be extended to cater to the needs of other types

of SBEs, which can be a potential topic for future research. The issues are different if the SBE

is not a house. For example, as the scale and scope of the project changes, the team assembly

will change significantly. The client base is different, so the collection of requirements is also

different. Technology decision and implementation approaches will also vary significantly

based on use cases. Hence, the framework needs to be customized by including specific

criteria for each use case. This is a potential domain for future research. Another limiting

factor is that some of the case study participants for developing dissemination strategies

were familiar with our research to some extent, which could have potentially biased their

feedback. Moreover, we did not conduct case studies on architectural design teams for

developing dissemination strategies. Future research can be directed towards addressing

these issues.

Target users of this framework are designers, researchers, and practitioners of smart homes

for developing design templates for on-site construction, or template modules for manufac-

tured housing, or one-off designs. Our framework/approach redefines the architect’s involve-

ment in the smart home design process, requiring them to have a bigger part in the design

process for innovative solutions through combining the architectural process with technolog-

ical aspects. The framework is also aimed to support researchers in developing innovative

smart home design solutions. For example, we observed during the ethnographic studies that

designers took the approach of building houses as we build cars, i.e., developing core func-

tionalities (kitchen, bathroom, home-office, etc.) as factory-built, wired modules designed

with integrated spatial and technological considerations. Our framework promotes this type

of innovative design solutions by offering a holistic perspective that integrates HCI, HBI,

and architecture. Architectural and smart home practitioners can follow the framework step-

141

by-step throughout the design process. In its current form, the framework is most suitable

for two types of users. The first type is a design team of one-off projects, where the team is

commissioned to build a smart house. Second type is a design team of builders for designing

templates for smart homes.

This framework addresses an interdisciplinary research problem which potentially requires

a new sort of domain experts who are trained on both architectural knowledge and tech-

nological issues. Our research points towards the emergence of a new discipline to train

domain experts accordingly. More than 90% of the homes in the USA are developed by

builders following a template-based design approach. Their process is design, bid, and build.

Therefore, a collaboration between builders, architects, and technology professionals can be

the ideal team to design innovative solutions for the home of the future.

The ArTSE framework lays out the ground work for developing a digital tool for assisting

the smart home design process. The digital tool can be used to support the use of this

framework. The tool can incorporate visual components to support the inputs and outputs

of different phases of the framework. It can also be conceptualized as having two modes– one

for supporting the designers in decision making/layout design, and another for supporting

the occupants/clients in expressing and visualizing their requirements. Existing tools, like

SketchUp, Revit, etc. could also be upgraded to support design thinking by including a rep-

resentation of the framework. Communication with clients/stakeholders can be made easier

with digital tools by making it interactive, using visual components, and easily accessible.

For example, prototyping has an important role in the design process, but prototype building

can be expensive and time consuming. This sort of digital tool can address this issue by

leveraging technological solutions like VR/MR-based simulations for testing out interaction

techniques (e.g, voice, gesture, etc.) or architectural layouts (virtual walk-through).

Overall, our research addresses a nascent research problem at the intersection of HCI, HBI,

142 Chapter 7. Conclusion

and architecture, where the architectural and technological aspects are brought together

to start an interdisciplinary collaboration. To that end, our aim is to disseminate this

framework so that this acts as a process guideline for smart home projects. We target the

designers, researchers, and practitioners of smart homes as potential users of this framework.

We aim to use workshops, presentations, and booklets to get the framework in the hands

of the target users. The domain of future research consists of evolution of the framework

based on use cases. Future directions can include exploring the changes in the framework if

the SBE is not a residence, rather an office building, or an educational institute, or a retail

property, or any other type of built environment. We hope that the research presented in

this dissertation will help close the gap in design thinking for smart environment design and

help reimagine smart homes.

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Appendices

163

Appendix A

Incremental Development of SBE

Design Framework

Here we include the document that contains the incremental development of the ArTSE

framework.

164

We want to avoid this…

Step 1:

Problem Definition

Step 2: Information Collection

Step 3:

Concept & Schematic

Design

Step 4: Design

Development

Step 5:

Presentation & Evaluation

Step 6:

Modify Design

Step 7:

Construction Drawing

Traditional Architectural Design Process

Phase 1: Schematic

Design

Phase 2: Design

Development

Phase 3: Presentation & Evaluation

Phase 4: Construction

ProgramAnalysis

Information Collection

HCI Models

Concept & Schematic Design

Design Development

TechnologyIntegration

InteractionTechniques

Presentation & Evaluation

Working Drawing

Bidding & Construction

1.1 1.2 1.3 1.4

2.1 2.2 2.3

3.1

Detail Development

4.1 4.2 4.3

Data Integration

Baseline Framework for SBE Design

SystemArchitecture

2.4 2.5

Phase 1: Ideation

Phase 2: General Study

Phase 3: Development

Phase 4: Implementation

ProgramAnalysis

Info Collection

HCI Models

Outline Proposal

Client Feedback

SchemeDesign

TechnologyDecision


Detail Design

TechnologyInfrastructure

MakePrototype

Client Feedback

Client Feedback

Working Drawing


1.1 1.2 1.3 1.4 1.5

2.1 2.2 2.3

3.1 3.2 3.3 3.4

4.2

Presentation

4.1 4.3 4.4Client

Feedback

Proposed Framework: Iteration 1 (version 1)

2.4

Phase 1: Assimilation




ProgramAnalysis

Info Collection

HCI Models

Outline Proposal

Client Feedback

SchemeDesign

TechnologyDecision


Detail Design


Cost Estimate

Client Feedback

Client Feedback

Working Drawing


1.1 1.3 1.4 1.5

2.1 2.2 2.3

3.1 3.2 3.3

Presentation

4.1 4.2 4.3

Client Feedback

Team Composition

1.2

Cost Estimate

2.4

3.4

MakePrototype

Proposed Framework: Iteration 1 (version 2)

Phase 1: Ideation




Initial ProgramAnalysis

HCI models for Info Collection

Pitch

Client Feedback

SchemeDesign

TechnologyDecision


Detail Design


Cost Re-evaluation

Client Feedback

Client Feedback

Working Drawing


1.1 1.3 1.4

2.1 2.2 2.3

3.1 3.2 3.3

Presentation

4.1 4.2 4.3

Client Feedback

Team Composition

1.2

Cost Estimate

2.4

3.4

MakePrototype

Inspection

4.4

Proposed Framework: Iteration 2

Prototype

Client Feedback

External Consultants

Phase 1: Ideation




Program + BudgetAnalysis


Proposal outline + Cost Estimate

+ Client EducationClient Feedback

SchemeDesign

TechnologyDecision

InteractionDesign

Client Feedback

Working Drawing


1.1 1.3 1.4

2.1

2.2

2.3

Presentation

4.1 4.2 4.3

Team Assembly

1.2

Cost+TimeEstimate

2.4

Inspection

4.4

Pitch

Client Feedback


Detailed Design

Technology Infrastructure

3.4

3.1

3.2

Cost Re-evaluation

3.3

Evaluation + Testing

Proposed Framework: Iteration 3, v1

Prototype

Client Feedback


Phase 1: Ideation




Program + BudgetAnalysis


Concept Development

+ Cost Estimate+ Client EducationClient Meeting

SchemeDesign

TechnologyDecision

InteractionDesign

Client Feedback

Working Drawing


1.1 1.3 1.4

2.1

2.2

2.3

Presentation

4.1 4.2 4.3

Team Assembly

1.2

Cost+TimeEstimate2.4

Maintenan-ce

4.4

Pitch

Client Feedback


Detailed Design

Technology Infrastructure

3.4

3.1

3.2

Cost Re-evaluation

3.3

Evaluation + Testing

Proposed Framework: Iteration 3, v2Exists in traditional architectural process and significantly changes in SBE

Unique to SBE, does not occur in traditional architectural process

Concept DiagramsProposed Web-based ``Design Your Dream House'' Tool for Occupants for Streamlining Design Process

Concept: Proposed Schematic Design Tool

Sleep/restEntertainHome officeCookDinePersonal HygieneIndoor-outdoor

Allocated area

Activity based design

Kitchen

Bath


Entertain, home office Sleep/rest

Required Area120 sft100 sft80 sft

Bed Bath Veranda

Drag and Drop: Plan View

Modules

Living Kitchen

Living Bed

Kitchen Bath


Schematic Plan Total Estimated Cost

Smart Technology Focus Area

Living Bed

Kitchen Bath

Vendors Price

Lutron

Philips

$X

$Y

Equipment Count Estimate

Light 5 5X

Height-adjustable Sink

3 3Z

Kohler $Z

Vendor

Lutron

Kohler

Comfort EnergyConservation

Ageing in placeSecurity


Appendix B

User Study: Individual, In-depth

Interviews

We conduct a survey to gather information about SBE design goals, design processes, and

best practices. The survey takes approximately 45 minutes to complete. Users receive a 10$

Amazon gift card for participating in the study. We have included the IRB-approved user

study description and questionnaire in this section.

Title: Best Practices and Guidelines for Smart Built Environment (SBE) Design

Process Focusing on Residences

Protocol No.: IRB-20-716

Users are eligible to participate if they have previously worked in a smart built environment

(SBE) project, preferably a smart residence project. Participants have two options—

1. Completing the questionnaire asynchronously.

2. Scheduling an audio/video conference call to complete the survey in an online interview

format.

178

B.1. Questionnaire 179

B.1 Questionnaire

The following questionnaire was developed using the Qualtrics Survey Software. The user

would participate in this survey using the online tool provided by Qualtrics.

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Summary

Q1.Information Sheet: Principal Investigator: Dr. Denis GračaninIRB# and Title of Study: IRB-20-716: Best Practices and Guidelines for Smart BuiltEnvironment (SBE) Design Process Focusing on ResidencesSponsor: Center for Human Computer Interaction User Study Funding Program

You are invited to participate in a research study. You are eligible to participate if you have previously

worked in a smart built environment (SBE) project, preferably a smart residence project.

“I am a graduate student at Virginia Tech, and I am conducting this study as part ofmy PhD research.”—Archi Dasgupta ([email protected]).

Ø WHAT SHOULD I KNOW?

If you decide to participate in this study, you can opt for one of the following options—

1. You can complete the questionnaire asynchronously.

2. You can schedule an audio/video conference call to complete the survey in an online interview

format by contacting Archi Dasgupta ([email protected]). The interview will not be recorded.

The survey aims to gather information about best practices for SBE design, goals, design processes,

and best practices. The study should take approximately 45 minutes. We do not anticipate any risks

from completing this study.

You can choose whether to be in this study or not. If you volunteer to be in this study, you may withdraw

at any time without consequences of any kind. The investigator may withdraw you from this research if

circumstances arise which warrant doing so.

Ø CONFIDENTIALITY

We will do our best to protect the confidentiality of the information we gather from you, but we cannot

guarantee 100% confidentiality.

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Any data collected during this research study will be kept confidential by the researchers. The

interviewer will take notes to transcribe the answers and code the transcripts using a pseudonym.

Transcriptions will be uploaded to a secure password-protected computer in the researcher’s office. The

researchers will maintain a list that includes a key to the code. The master key and the recordings will be

stored for 3 years after the study has been completed and then destroyed.

Ø WHO CAN I TALK TO? If you have any questions or concerns about the research, please feel free to contact Archi Dasgupta([email protected]). You are not waiving any legal claims, rights or remedies because of your participationin this research study. If you have questions regarding your rights as a research participant, contact theVirginia Tech HRPP Office at 540-231-3732 ([email protected]). Please print out a copy of this information sheet for your records.If you would like to participate in this survey, at least 18 years old and not a student of theinvestigators, click yes to begin or no to exit.

Demographic Information

Q2. Demographic Information

Respondent's experience with SBE design

Q3. How many years of experience do you have?

Q4. Please provide the number of SBE projects you have worked on for thefollowing categories.

Yes

No

Name

Email

Occupation & Affiliation

Area of Expertise

Regular Built Environment Project

Smart Built Environment (SBE) Project

Residential

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Q5. What was your role on the most representative smart residence project?(select all that apply)

Follow up questions on the project mentioned in Q11.

Q6.What were the reasons for choosing to construct an SBE versus a regular builtenvironment? (select all that apply)

Office

Educational

Retail

Other (please specify)

Project Name

Architectural Designer

Technology Consultant

Electrical Engineer

Mechanical Engineer

Project Manager

Civil Engineer

Construction Professional

Computer Scientist


Efficient Functionality and Convenience

Energy Conservation

Cost Efficiency

Healthcare (ageing in place, addressing disability)

Solving Spatial Limitation

Comfort

Security/Safety


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Q7. Which types of smart functionalities do clients typically want? (select all thatapply)

Q8. Which types of smart interaction techniques do clients typically want? (selectall that apply)

Q9. How did the inclusion of smart functionality affect the architectural design?(select all that apply)

Q10. During the SBE design process and selecting smart technology, what werethe main challenges? (select all that apply)

Smart Lighting

Smart Programmable Thermostat

Smart Security System

Automated Control of Doors/Windows

Healthcare Technology

Smart Meter

Reconfigurable Space


Physical Switch

Mobile Phone Application

Voice-based Interaction

Gesture-based Interaction

Mixed Reality-based Interaction


Architectural elements (wall, doors, windows etc.) embedded with sensors/actuators

Reconfigurable spaces

Smart surfaces as interfaces


Absence of a well-defined design framework for combining smart technology design withspatial design

Absence of unified technology solutions for supporting heterogeneous smart devices

Lack of established comparative metrics for choosing smart technology

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Q11.What are the main phases/steps that you followed during the SBE design process?(select all that apply)

Q12. In which phase was the decision made to construct an SBE versus a regularbuilt environment?

Q13. How did the decision to construct an SBE affect your design process? (selectall that apply)

Limited data source for smart technology


Ideation

Schematic Design

Design Development

Implementation


Ideation

Schematic Design

Design Development

Implementation


"Ideation" and "Design" phases changed significantly

Clients needed to be educated about smart home technologies

Needed additional steps for designing technology aspects

Needed counsel from technology consultants (smart technology experts, vendorrepresentatives, specialized engineers).

Time and cost of the project was affected significantly


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Q14. How did you collect requirements and feedback from clients? (select all thatapply)

Q15. Please rate the following statements for SBE design process:

Q16. Main activities in each phase:

Q17. Please include anything else you like to comment on which is not covered bythe questionnaire.

Meetings

Idea-images

Co-design Workshops

Prototype Building

Simulations


StronglyDisagree

SomewhatDisagree Neutral

SomewhatAgree

StronglyAgree

An user-centeredapproach for SBEdesign process isnecessary.

Existingperformance metricsfor evaluating SBEdesign are sufficient.

Existing simulationtools for simulatingSBE performanceare sufficient.

Regular inspectionduring constructionphase is necessary.

Ideation

Schematic Design

Design Development

Implementation


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Q18. Please provide your opinion about how the ongoing COVID-19 pandemic canaffect smart home design.

Q19.Please provide your feedback about the SBE design framework developed by theresearchers.We divided the design process into four phases.

Phase 1 - Ideation (color code - Yellow): Collecting project requirements andcreating initial idea pitch for clients.

Phase 2 - General Study (color code - Blue): Making the technology decisions anddeveloping a schematic design.

Phase 3 - Development (color code - Orange): Developing detailed architecturaldesign and technology infrastructure.

Phase 4 - Implementation (color code - Green): Finalizing design drawings andconstruction.

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Framework:

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