1

ABSTRACT

Ambient intelligence is an emerging discipline that brings intelligence to our everyday

environments and makes those environments sensitive to us. Ambient intelligence (AmI)

research builds upon advances in sensors and sensor networks, pervasive computing, and

artificial intelligence. Because these contributing fields have experienced tremendous growth in

the last few years, AmI research has strengthened and expanded. Because AmI research is

maturing, the resulting technologies promise to revolutionarize daily human life by making

people's surroundings edible and adaptive.

Ambient Intelligence (AmI) refers to a vision of the future information society where intelligent

interfaces enable people and devices to interact with each other and with the environment.

Today, most of the technologies needed for the realization of this vision are next-generation

technologies that are not currently on the market, but are being researched by research institutes

and corporate laboratories worldwide. In Europe, the IST Advisory Group (ISTAG) and the FP6

IST programme are strong promoters of the AmI vision. This article gives a short overview of

AmI, focuses on its role in everyday life and identifies some of the major challenges and

bottlenecks facing the concept. The paper argues that, although people are presented as at the

core of the vision, AmI would benefit from a more substantial everyday life perspective that

confronts users in their everyday lives with future visions and technologies.

2

TABLE OF CONTENTS

Sr. No. Topics Page No.

1. Introduction 1-2

2. History 3-4

3. Technology Used 5-8

4. Steps of Ambient Intelligence 9-10

5. Applications 11-13

6. Issues 14-16

7. Research work 17

8. Future Scope 18

9. Conclusion 19

10. References 20

3

INTRODUCTION

Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to

the presence of people. Ambient intelligence is a vision on the future of consumer electronics,

telecommunications and computing that was originally developed in the late 1990s for the time

frame 2010–2020. In an ambient intelligence world, devices work in concert to support people in

carrying out their everyday life activities, tasks and rituals in an easy, natural way using

information and intelligence that is hidden in the network connecting these devices (see Internet

of Things). As these devices grow smaller, more connected and more integrated into our

environment, the technology disappears into our surroundings until only the user interface

remains perceivable by users.

The ambient intelligence paradigm builds upon pervasive computing, ubiquitous computing,

profiling, context awareness, and human-centric computer interaction design and is characterized

by systems and technologies that are:

embedded: many networked devices are integrated into the environment

context aware: these devices can recognize you and your situational context

personalized: they can be tailored to your needs

adaptive: they can change in response to you

anticipatory: they can anticipate your desires without conscious mediation.

AmI refers to a digital environment that proactively, but sensibly, supports people in their

everyday lives. It will make the feeling that the people live with technology. It is aligned with the

concept of ‘disappearing computer’, since the AmI environment make the technology invisible.

As the devices grow smaller, more connected and more integrated into our environment, the

technology disappears into our surroundings. “The most profound technologies are those that

disappear. They weave themselves into the fabric of everyday life until they are indistinguishable

from it.” M. Weiser The basic idea behind AmI is that by enriching an environment with

technology (mainly sensors and devices interconnected through a network), a system can be built

to take decisions to benefit the users of that environment based on real-time information gathered

and historical data accumulated.

4

An important aspect of AmI has to do with interaction. On one side there is a motivation to

reduce the human-computer interaction as the system is supposed to use its intelligence to infer

situations and user needs from the recorded activities, as if a passive human assistant was

observing activities unfold with the expectation to help when (and only if) required. On the other

side, a diversity of users may need or voluntarily seek direct interaction with the system to

indicate preferences and needs. The entire environment around us, homes and offices, cars and

cities, will collectively develop a pervasive network of intelligent devices that will cooperatively

gather, process and transport information.

Ambient intelligence is closely related to the long term vision of an intelligent service system in

which technologies are able to automate a platform embedding the required devices for powering

context aware, personalized, adaptive and anticipatory services. Where in other media

environment the interface is clearly distinct, in an ubiquitous environment 'content' differs. Artur

Lugmayr defined such a smart environment by describing it as ambient media. It is constituted of

the communication of information in ubiquitous and pervasive environments. The concept of

ambient media relates to ambient media form, ambient media content, and ambient media

technology. Its principles have been established by Artur Lugmayr and are manifestation,

morphing, intelligence, and experience. A typical context of ambient intelligence environment is

a Home environment.

Ambient Intelligence is based on the key technologies: Ubiquitous Computing, Ubiquitous

Communication and Intelligent User Interface.

Ubiquitous Computing means the integration of microprocessors into everyday objects

like furniture, clothes or toys.

Ubiquitous Communication should enable these objects to communicate with each other

and with the user.

Intelligent User Interface enables the inhabitants of the AmI to control and interact with

the environment in a natural (voice, gestures) and personalized way (preferences,

context).

5

HISTORY

In 1998, the board of management of Philips commissioned a series of presentations and internal

workshops, organized by Eli Zelkha and Brian Epstein of Palo Alto Ventures (who, with Simon

Birrell, coined the name 'Ambient Intelligence') to investigate different scenarios that would

transform the high-volume consumer electronic industry from the current “fragmented with

features” world into a world in 2020 where user-friendly devices support ubiquitous information,

communication and entertainment. While developing the Ambient Intelligence concept, Palo

Alto Ventures created the keynote address for Roel Pieper of Philips for the Digital Living Room

Conference, 1998. The group included Eli Zelkha, Brian Epstein, Simon Birrell, Doug Randall,

and Clark Dodsworth. In the years after, these developments grew more mature. In 1999, Philips

joined the Oxygen alliance, an international consortium of industrial partners within the context

of the MIT Oxygen project, aimed at developing technology for the computer of the 21st

century. In 2000, plans were made to construct a feasibility and usability facility dedicated to

Ambient Intelligence. This HomeLab officially opened on 24 April 2002.

Figure: A timeline of key events and publications on Ambient Intelligence

Along with the development of the vision at Philips, a number of parallel initiatives started to

explore ambient intelligence in more detail. Following the advice of the Information Society and

Technology Advisory Group (ISTAG), the European Commission used the vision for the launch

of their sixth framework (FP6) in Information, Society and Technology (IST), with a subsidiary

6

budget of 3.7 billion euros. The European Commission played a crucial role in the further

development of the AmI vision. As a result of many initiatives the AmI vision gained traction.

During the past few years several major initiatives have been started. Fraunhofer Society started

several activities in a variety of domains including multimedia, microsystems design and

augmented spaces. MIT started an Ambient Intelligence research group at their Media Lab.

Several more research projects started in a variety of countries such as USA, Canada, Spain,

France and the Netherlands. In 2004, the first European symposium on Ambient Intelligence

(EUSAI) was held and many other conferences have been held that address special topics in

AmI.

7

TECHNOLOGY USED

Ambient Intelligence is based on the three key technologies:-

Ubiquitous Computing

Ubiquitous computing is a concept in software engineering and computer science where

computing is made to appear everywhere and anywhere. In contrast to desktop computing,

ubiquitous computing can occur using any device, in any location, and in any format. A user

interacts with the computer, which can exist in many different forms, including laptop

computers, tablets and terminals in everyday objects such as a fridge or a pair of glasses. The

underlying technologies to support ubiquitous computing include Internet, advanced middleware,

operating system, mobile code, sensors, microprocessors, new I/O and user interfaces, networks,

mobile protocols, location and positioning and new materials.

Ubiquitous Communication

Ubiquitous Communication enables these objects to communicate with each other and the user

by means of ad-hoc and wireless networking.

Intelligent User Interface

An intelligent user interface (Intelligent IU, IUI, or sometimes Interface Agent) is a user

interface (UI) that involves some aspect of Artificial Intelligence (AI or Computational

Intelligence). There are many modern examples of IUIs, the most famous (or infamous) being

the Microsoft Office Assistant, whose most recognizable agentive representation was called

"Clippy".

Generally, an IUI involves the computer-side having sophisticated knowledge of the domain

and/or a model of the user. These allow the interface to better understand the user's needs and

personalize or guide the interaction.

8

A variety of technologies can be used to enable Ambient intelligence environments such as:-

Bluetooth Low Energy

Bluetooth low energy or Bluetooth LE, marketed as Bluetooth Smart, is a wireless personal area

network technology designed and marketed by the Bluetooth Special Interest Group aimed at

novel applications in the healthcare, fitness, beacons, security, and home entertainment

industries. Compared to Classic Bluetooth, Bluetooth Smart is intended to provide considerably

reduced power consumption and cost while maintaining a similar communication range.

Radio Frequency Identification:

Radio-frequency identification (RFID) is the use of a wireless non-contact system that uses

radio-frequency electromagnetic fields to transfer data from a tag attached to an object, for the

purposes of automatic identification and tracking. Some tags require no battery and are powered

by the electromagnetic fields used to read them. Others use a local power source and emit radio

waves (electromagnetic radiation at radio frequencies). The tag contains electronically stored

information which can be read from up to several meters (yards) away. Unlike a bar code, the tag

does not need to be within line of sight of the reader and may be embedded in the tracked object.

Microchip implant (human):

A human microchip implant is an integrated circuit device or RFID transponder encased in

silicate glass and implanted in the body of a human being. A subdermal implant typically

contains a unique ID number that can be linked to information contained in an external database,

such as personal identification, medical history, medications, allergies, and contact information.

Sensor:

A sensor (also called detector) is a converter that measures a physical quantity and converts it

into a signal which can be read by an observer or by an (today mostly electronic) instrument. For

example, a mercury-in-glass thermometer converts the measured temperature into expansion and

contraction of a liquid which can be read on a calibrated glass tube. A thermocouple converts

temperature to an output voltage which can be read by a voltmeter. For accuracy, most sensors

are calibrated against known standards.

9

Sensors are used in everyday objects such as touch-sensitive elevator buttons (tactile sensor) and

lamps which dim or brighten by touching the base. There are also innumerable applications for

sensors of which most people are never aware.

Software Agent:

Software agent is a software program that acts for a user or other program in a relationship of

agency, which derives from the Latin agere (to do): an agreement to act on one's behalf. Such

"action on behalf of" implies the authority to decide which, if any, action is appropriate.

Related and derived concepts include Intelligent agents (in particular exhibiting some aspect of

Artificial Intelligence, such as learning and reasoning), autonomous agents (capable of

modifying the way in which they achieve their objectives), distributed agents (being executed on

physically distinct computers), multi-agent systems (distributed agents that do not have the

capabilities to achieve an objective alone and thus must communicate), and mobile agents

(agents that can relocate their execution onto different processors).

Affective Computing:

Affective computing is the study and development of systems and devices that can recognize,

interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer

sciences, psychology, and cognitive science. While the origins of the field may be traced as far

back as to early philosophical enquiries into emotion, the more modern branch of computer

science originated with Rosalind Picard's 1995 paper on affective computing. A motivation for

the research is the ability to simulate empathy. The machine should interpret the emotional state

of humans and adapt its behavior to them, giving an appropriate response for those emotions.

Nanotechnology:

Nanotechnology is very diverse, ranging from extensions of conventional device physics to

completely new approaches based upon molecular self-assembly, from developing new materials

with dimensions on the nanoscale to direct control of matter on the atomic scale.

Nanotechnology entails the application of fields of science as diverse as surface science, organic

chemistry, molecular biology, semiconductor physics, micro fabrication, etc.

10

Scientists debate the future implications of nanotechnology. Nanotechnology may be able to

create many new materials and devices with a vast range of applications, such as in medicine,

electronics, biomaterials and energy production. On the other hand, nanotechnology raises many

of the same issues as any new technology, including concerns about the toxicity and

environmental impact of nanomaterials, and their potential effects on global economics, as well

as speculation about various doomsday scenarios. These concerns have led to a debate among

advocacy groups and governments on whether special regulation of nanotechnology is

warranted.

Biometrics:

Biometrics refers to the identification of humans by their characteristics or traits. Biometrics is

used in computer science as a form of identification and access control. It is also used to identify

individuals in groups that are under surveillance.

Biometric identifiers are the distinctive, measurable characteristics used to label and describe

individuals. Biometric identifiers are often categorized as physiological versus behavioral

characteristics. A physiological biometric would identify by one's voice, DNA, hand print or

behavior. Behavioral biometrics is related to the behavior of a person, including but not limited

to: typing rhythm, gait, and voice. Some researchers have coined the term behaviometrics to

describe the latter class of biometrics.

11

STEPS OF AMBIENT INTELLIGENCE

Main steps of Ambient Intelligence:

1. Sensing

Sensors

Ambient or body

12

2. Reasoning

Needed to provide responsiveness and adaptability

Interpret and recognize context and activity

Context detection and context awareness

Mobility tracking

Activity recognition, activity prediction

Decision making

3. Acting

Home automation systems (lights, doors, windows, temperature…)

User Interfaces or Wearable devices (notification, information, alerting…)

Robots

4. Interacting with Users

Traditional user interfaces: web, mobiles

Home fixtures

Natural user interfaces:

Speech, gesture, body motion tracking, emotions, facial expressions,

attention…

Interaction bypasses ICT equipment(“disappearing computer”)

13

APPLICATION

The various applications where ambient intelligence can be used:-

Smart Homes:

Ambient Intelligence is allowing the home itself to possess intelligence and make decisions

regarding its state and interactions with its residents. The AmI specification may include the

Meaningful environment is the house, including the backyard and a portion of the front door as

these areas also have sensors. Objects are plants, furniture, and so on.

Health – Related Applications:

Hospitals can increase the efficiency of their services by monitoring patients’ health and progress

by performing automatic analysis of activities in their rooms.

Health services at hospitals could use a link to patients home via a mobile phone to health

sensors, for example, during recuperating from an operation or during long-term treatment of

some disease, e.g. cancer.

Public Transportation sector:

Public transport can benefit from extra technology including satellite services, GPS-based spatial

location, vehicle identification, image processing and other technologies to make transport more

fluent and hence more efficient and safe.

Based on the time needed to connect two locations with sensors, the system can also predict the

speed of each unit. Examples of objects in this environment are tracks and stations. Interactors

are trains, drivers and command centre officers. Sensors are used for identification purposes

based on ID signals sent from the train. Other signals can be sent as well, e.g., emergency status.

Actuators will be signals coordinating the flow of trains and messages that can be delivered to

each unit in order to regulate their speed and the time they have to spend at a stop. Contexts of

interest can be “delays” or “stopped train”. One interaction rule can be “if line blocked ahead and

there are intermediate stops describe the situation to passengers”.

14

Education Services:

Education-related institutions may use technology to create smart classrooms where the modes of

learning are enhanced. The objects within a classroom or play ground are tables and other

available elements. The interactors are students and teachers. The sensors will identify who is

using what scientific kit and that in turn will allow monitoring of how long students are involved

with a particular experiment. Actuators can be recommendations delivered to wristwatch-like

personalized displays. Contexts of interest can be “student has been with a single

experimentation kit for too long” or “student has not engaged in active experimentation”. The

first context will trigger a rule “if student has been interacting with one single kit for more than

20 minutes advise the student to try the next experiment available” whilst the second one can

send a message to a tutor, such as “if student has not engaged for more than 5 minutes with an

experiment then tutor has to encourage and guide the student”.

Emergency services:

Safety-related services like fire brigades can improve the reaction to a hazard by locating the

place more efficiently and also by preparing the way to reach the place in connection with street

services.

Streets can be equipped with sensors to measure passage of traffic within the areas through

which the fire brigade truck might go through in order to reach the place where the emergency is

located. Objects here will be streets and street junctions. Interactors will be cars. Actuators can

be traffic lights as they can help speed the fire brigade through. A context will be a fire occurring

at peak time with a number of alternative streets to be used. An interaction rule can be “if all

streets are busy, use traffic lights to hold traffic back from the vital passage to be used”.

Production-oriented places:

Companies can use RFID sensors to tag different products and track them along the production

and commercialization processes. This allows identifying the product path from production to

consumer and helps improving the process by providing valuable information for the company

on how to react to favorable demand and unusual events like products that become unsuitable for

sale.

15

Sensors can track the flow of items at critical bottlenecks in the system and the system can

compare the current flow with a desired benchmark. Decision makers can then take decisions on

how to proceed and how to react to the arrival of new materials and to upcoming demands.

Different parts of the plant can be de/activated accordingly. Similarly, sensors can provide useful

information on places where there has been a problem and the section has stopped production,

requiring a deviation in flow. Objects here are transportation belts and elements being

manufactured whilst actuators are the different mechanisms dis/allowing the flow of elements at

particular places. A context can be “a piece of system requiring maintenance” and a related

interaction rule can be “if section A becomes unavailable then redirect the flow of objects

through alternative paths”.

Public Surveillance

Sensors are enriched CCTV cameras on street or on transport, monitored by security guards.

Integrators are law abiding citizens and potential muggers. A context can be “if a person is

attacked, provide an alarm, issue a verbal warning in-situ to deter attacker and activate a rescue

from the nearest police station or security guard”. Bidirectional voice channels can be used. Of

course AmI requires that the sensing, decision making and actuator are automated. In future this

can be achieved with image and sound processing, reasoning for the identification of an

emergency situation and text-to-speech warnings delivered to the offender.

16

ISSUES

Social issues

In order to be accepted, AmI must be driven by primarily humanistic and not technological

goals. It is assumed that everyday life skills will rise because of rising opportunities and means

of personal expression and interaction. At work too there are likely to be rising skill demands.

Some will be higher requirements for the technological expertise, but if the AmI manifesto is to

be achieved the main skills rise will be in social know-how and information manipulation.

Therefore, there are still many vague issues, some of which may not become clear until AmI

becomes reality. Can AmI reduce (mental) health risks from information stress, virtual identities

and information overloads? There is also already discussed issue: privacy. Technological

developments are outpacing regulatory adjustments. To what extent can people be protected in

AmI landscape? Furthermore, AmI should be controllable by the ordinary people; otherwise

there will be a lack of social acceptance. So, there is a need for developing technologies which

will enable people to decide what level of access they have and when. Besides, the privacy is not

only issue that may endanger the acceptance of Ambient Intelligence. We must not neglect that

there are people who simply do not like this vision. Regardless of privacy. This will also be a

great challenge for the supporters of Ambient Intelligence. Encouraging sound the word of Mark

Weiser:

“Ubiquitous computing is roughly the opposite of virtual reality, where virtual reality puts people

inside a computer-generated world; ubiquitous computing forces the computer to live out here in

the world with people.”

Business issues

An interested reader may pose the following questions: Who will make AmI work? Who will

produce it? Who will make money? How will AmI change the way people work, think and

learn? These are all undoubtedly hard questions. On the other hand, some developments can be

predicted even now.

17

According to the ISTAG report, the new emerging business landscape will have the following

features:

Initial premium value niche markets where interfaces are needed to support human

performance in fast moving and highly delicate situations.

High access-low entry cost based on a loss leadership model in order to create economies

of scale.

Self-provision models based upon the network of very large user communities providing

information at near zero cost. As for the way the companies act in the market, the most

spread form will be partnerships and that due to two reasons. Firstly, very large sums of

investment are involved. Secondly, the technological developments require cross-

disciplinary and cross-sectoral capabilities.

Technological issues

A set of common technological requirements would look like this:

Hardware must be “very unobtrusive”. The reasons for this are pretty obvious, since AmI

must be nearly invisible. It is thus necessary to make detailed researches in micro and

optical electronics. Molecular and atomic manipulation techniques will be needed to

produce smart materials and nanotechnologies. Besides, technologies needed to

develop “mechanisms” for self-generating power usage in objects are also necessary.

A seamless mobile/fixed web-based communications infrastructure needs to be

developed, for ubiquitous communication demands omnipresent communication. But, it

is clear that the networks will be very heterogeneous and complex. Therefore, it is

necessary to completely integrate mobile and fixed and radio and wired networks.

Probably all the networks will be operating with some equivalent of the IP technology.

In the AmI world there will be uncountable interoperating devices. What is necessary

here is that networks be configurable on the ad hoc basis due to a specific task with

variable actors and components. As for databases, they should be accessible on demand

from anywhere in the system.

The greatest challenge would consist in creating systems that are intuitive in use. Here we

point to the important role of artificial intelligence. There is also need for developing

18

interfaces able to recognize speech and gesture as well as those that are context sensitive

and capable of information filtering and presentation.

There will be a great demand to provide security in such an environment. We have

already discussed how sensitive this matter is in terms of social acceptance. But it is the

task of technicians to provide the needed security, i.e. systems that are secure against

deliberate misuse. The possible techniques are ID authentication, micropayment systems

or biometrics (fingerprints, iris scanning, and speech).

19

RESEARCH WORK

Research in Ambient Intelligence is proceeding at a tremendous pace, but so far outcomes have

been witnessed in specific domains and specific applications. Various required technologies for

ambient intelligence are already available, including smart mobile phones, sensors, ad-hoc

networks, and computing, but still requiring some advancements in their integration and

scalability. Some technological advancement that are helping to realize ambient intelligence

include energy scavenging wireless sensors, advancements in RFID technology by

nanoelectronics, specialized low power radio for sensor communication like Ultra

Low Power (ULP) Bluetooth and integration technology like MEMS. Below is a brief

description of the work done in the areas of physical selection, local and wireless sensor

connectivity, context awareness, natural multimodal interfaces, and sensors connected to internet

services.

The products which have been researched are as follows:-

Internet Fridge

Karotz

Moores Cloud

HomeOS

SmartTvs

CeNSE

Connected Cars

20

FUTURE SCOPE

Ambient Intelligence is establishing fast as an area where a confluence of topics can coverage to

help society through technology. There are still many challenges ahead and improvements are

needed at all levels: infrastructure, algorithms and human-computer interaction for AmI systems

to be widely accepted and more important of all, be useful to society.

Many AmI applications relying upon wireless sensors are at the mercy of the battery life for the

sensors. Challenge is to model multiple residents in an environment. Challenge for AmI

researches is to design self-testing and self-repairing AmI software. Issues related to security and

privacy for AmI systems.

21

CONCLUSION

The introduction of AmI in a home environment will have an impact on personal lives in several

ways. The time gained will allow people to spend more time with their family and friends.

Convenience, money, time savings, security, safety and entertainment reduce the stress leading

to an overall higher quality of life. However, the ability to prepare or complete more and more

everyday tasks such as shopping or banking at home, potentially leads to reduced face-to-face

interaction between people or, at least, to selective interaction restricted to mainly family and

friends.

The disadvantage is that every node and the system as a whole need protection.

Research must, therefore, focus on developing user-friendly low-cost solutions with a high level

of network security. Managers of the various companies intending to produce and sell AmI

technology must agree on common networking standards, which are a major factor determining

future success or failure.

22

REFERENCE

http://www.jaise-journal.org

http://www.dke.univie.ac.at/extern/bi.../ss2002/Ambient-Intelligence.pdf

http://www.irisa.fr/lande/lande/icse-proceedings/icse/p43.pdf

http://www.cse.hut.fi/en/publications/B/1/papers/Maheshwaree_final.pdf

http://www.idate.org/fic/revue_telech/418/CS57_PUNIE.pdf

http://www.seminarsonly.com/computer%20science/Ambient-Intelligence.php

http://www.research.philips.com/technologies/download/homelab_365.pdf

http://www.hitech-projects.com/euprojects/ambience

http://www.amfastech.com/2013/01/a-seminar-on-ambient- intelligence-ami.html