1 Automated Data Collection Technology Automated Quantities Reporting Spring 2008 Forest Peterson – Stanford Construction Engineering & Management

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Automated Data Collection Technology

Automated Quantities ReportingSpring 2008

Forest Peterson – Stanford Construction Engineering & Management

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List of ToolsIntegrated Scope-Cost-Schedule Model (BIM)Radio Frequency Identification (RFID) Micro-Electro-Mechanical Systems (MEMS)Ultra Wide-band (UWB)Equipment On-board Sensors (OBS)Global Positioning Satellites (GPS)Geographic Information System (GIS) Electronic Timecard and Invoices, field laptopsObject Character Recognition (OCR)Object Recognition3D – Imaging (LADAR)Electronic imaging[Data Mining], [network database]

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BETA Commercial SoftwareLocation Based Scheduling, Finland

Vico Control 2008

Take-off suite, Finland

TocomanInnovayaBuilding explorer

Estimating & production database, Finland

Sage-TimberlineHCSSMC2

Historical libraryRS Means

Middleware



Scheduling (Vico)3D Software (Revitt)Cost Accounting (Oracle Edward Jones)Forecasting (Federal Reserve)Document Control (Prolog)4D CAD (Navisworks)Quantity Collection (Field Engr. Excel)Takeoff (AGTEK)Software Integration (Vico, Oracle, Bentley)

Software Integration / BIMRadio Frequency Identification (RFID) Micro-Electro-Mechanical Systems (MEMS)Ultra Wide-band (UWB)Equipment On-board SensorsGlobal Positioning Satellites (GPS)Geographic Information System (GIS) Object Recognition 3D – ImagingElectronic imaging

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quantities

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map object-components

Cost ModelSage-Timberline

Process ModelVico Control

recipe formulas

publish quantities

MiddlewareTocoman Express

Hosted ServerTocoman Construction Model Server / Citrix

Takeoff QuantitiesTocoman Quantity

Manager

component-operations, quantities &

production rates

component-operations combined into

activitiescomponent-operations, unit cost & production

rates

component-operations, recipe formulas & production rates

Component-operation library

RS Means

estimator looks at process model and selects component-

operations

Building Information

ModelADT

MiddlewareTocoman Exchange

Object-component takeoff

Tocoman iLink4

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Estimated work in place

Integrated BIM scope-cost-time

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Quantities

Components, unit cost &

production rates

BIM Model(ADT)

Object Group Takeoff

(Tocoman ilink)

Library Database (Sage / RS Means)

Estimate(Sage-Timberline)

Project Takeoff(Tocoman Qty. Mgr.)

Schedule (Vico Control)

Estimator looks at model, develop project planning &

setup

Project Recipes

Publish Qtys.

Components, quantities &

production rates

Recipe components & production rates

Citrix Server (Tocoman Construction Model

Server)

Middleware(Tocoman Express)

Map Objects

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Update from teach integrated

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Product model

Cost model

Process model

Production library

Take-off recipe formulas

Object library

Classification through WBS

Customizable Database / knowledge

Human-computer interaction

Integrated or Middleware

Formula library

Exogenous object-

components

Planning & Setup

Endogenous components

Operations

SCOPE COSTTIMEQUALITY

project

Activity library

Budget library

Construction method

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Exogenous Explicit object-componentsEndogenous Implicit components

legend

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SimAL Software, XLS, ADTA Simulation Access Language and Framework

with Applications to Project Management, Jinxing Cheng, (2004) Stanford University

“Allow users to simulate different scenarios” and integrate software tools in search of optimum efficiency

Component of any project management tool is to allow multiple scenarios to be modeled

*see markel

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Interfaces for Searching, Managing, and Sharing Collected Field Data (template)

ButterflyNet: Mobile Capture and Access for Biologists, Yeh, Ron B; Klemmer, Scott R June 2005

http://dbpubs.stanford.edu:8090/pub/2005-27http://hci.stanford.edu/research/biology/

User Interface

Butterfly Net Meta data (WBS) link

Sensor-based

Direct Measurements

Field Notes/Photo

Potential Cost/Scheduling

System Connection



http://dbpubs.stanford.edu:8090/pub/2005-27

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Electronic Invoicing & Time Cards

• Standard Template• Formatted for automated

import to accounting or schedule software

• Account number assignment– Account number provided

with orderor

– Automated using type / time / location

– Automatically generated account numbers verified or cross referenced

Automated Quantities ReportingAutumn 2007

Forest Peterson – Stanford CEM

Materials, sub work, cost code structure mirrors sub billing

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Object Character Recognition (OCR) & Electronic Invoicing

Electronic invoicing & OCR technology has potential to automate quantity input.

Hathaway Dinwiddie Y2E2 project used scanning technology only for paperless archives. Could have used for data entry.

scan data

template match-up

lookup account number

transfer data to accounts

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Auto Mapped Links

Auto mapping to supplier server, government server, oversight, specifications, climate record, CIS

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Database Queries, Data Mining or Data Analysis, Auto Mapped Links

Example: hourly rates adjusted to compensate fuel

cost, requires periodic update from

.gov server



Gather data on suppliers, subs, owner, oversight, weather,

standards, technology improvements, forecasting.

Generate reliable quantity data from data sets collected by

sensors

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3D Imaging

http://www.trimble.com/trimblegx.shtml

http://www.leica-geosystems.com

NIST - CMAG testing remote management of construction sites (Cheoka et al. 2006)

Jobsite Procedures to Allow 3D-Imaging (expand for other technologies)

Effective range is approximately 80 meters, park equipment in designated areas & store material in designated locationsCMU algorithm for scanner placement (Gordon et al. 2003)

Radio / preprogrammed control surveillance unit. Time critical information gathering http://www.dragonflypictures.com/

Surveillance and monitoring of ground based objectshttp://vertol.mit.edu/prjinfo.html

http://www.christopherholt.com/subjects/construction_00.htm

http://www.dragonflypictures.com/

http://www.rctoys.com






http://vertol.mit.edu/prjinfo.html

http://vertol.mit.edu/prjinfo.html

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3D Imaging

Smart Chips in Construction, (2002) William Stone, Alan Lytle and Karen Furlani, National Institute of Standards and Technology

I-Site• Stockpile• Truck load• Cut/Fill • http://www.isite3d.com

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Photographic quantity collection

Fard M. G., and Peña-Mora, F. "Application of Visualization Techniques for Construction Progress Monitoring" Proceeding of the 2007 ASCE International Workshop on Computing in Civil Engineering Lucio Soibelman, Burcu Akinci - Editors, July 24–27, 2007, Pittsburgh, Pennsylvania, USA

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“Construction Object Identification from LADAR Scans: An Experimental Study Using I-Beams,” (2005) Gilsinn, D.E., Cheok, G. S., Witzgall, C., and Lytle, A. National Institute of Standards and Technology

Object Recognition

“Combining Reality Capture Technologies for Construction Defect Detection: A Case Study” (2003) Gordon, C., Boukamp, F., Huber, D., Latimer, E., Park, K., and Akinci, B.

4D schedule updated

CPM-schedule updated

3D image acquired

from LADAR

object recognized

from library

Time & (X,Y,Z)

3D object library

updated

visual display

activity code

Expected time & place

Expected object

expected activity

NIST proposal A.Lytle http://www2.bfrl.nist.gov/projects/projcontain.asp?cc=8614102000

http://en.wikipedia.org/wiki/3D_single_object_recognition



Add other researchers

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“Performance Analysis of Next-Generation LADAR for Manufacturing, Construction, and Mobility”Ultra-wideband recommended for further research by (Stone et al. 2004) in NIST publication

“Complex Permittivity of Planar Building Materials Measured With an Ultra-Wideband Free-Field Antenna Measurement System” (Davis et al. 2007) early research on use of ultra wideband to collect quantities without line of sight requirement.http://en.wikipedia.org/wiki/Ultra-wideband

Ultra Wideband



http://en.wikipedia.org/wiki/Ultra-wideband

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Intelligent EquipmentVIRTUAL ROAD CONSTRUCTION – A CONCEPTUAL

MODEL (2007) Patrick Söderström and Thomas Olofsson eBygg – Center for IT in Construction, Luleå University of Technology, Sweden

- (information rich model) for applications: mass-optimization, estimation, planning, visualization, generation of machine data and follow-up.

- (DCI) support modifications. (Remove) Obstacles in contractual agreements between actors.

- PPC from real-time measures of locations of machine-guided (GPS) equipment.

Monitoring Construction Equipment for Automated Project Performance Control (2002) Rafael Sacks, Ronie Navon, Aviad Shapira and Irina Brodetsky - Technion - Israel Institute of Technology

“system for interpreting data acquired

automatically by monitoring the … equipment”



http://www.cat.com/cda/files/191058/7/AEHQ5549.pdf

http://en.wikipedia.org/wiki/Image:Img_613c.jpg

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Intelligent Equipment – onboard sensors

Past and Future of Construction Equipment, (2002) Cliff J. Schexnayder and Scott A. David, Arizona State University “Synthesized computers that instantly communicate by satellite with distant management teams reporting diagnostics, production, and position.”

http://www.cat.com/cda/layout?m=8703&x=7

Commercially Available GPS Fleet Tracking, GPS-based performance reports detailing the following fleet management criteria:Idle times, RPM’s, Odometer readings, Speed http://www.globalwave.com

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GPSTracking and locating components in a precast

storage yard utilizing radio frequency identification technology and GPS, (2006) Esin Ergen a, Burcu Akinci b, and Rafael Sacks c, Department of Civil Engineering, Istanbul Technical University, b Department of Civil and Environmental Engineering, Carnegie Mellon University, c Faculty of Civil and Environmental Engineering, Technion - Israel Institute of Technology

“… an automated system using radio frequency identification technology combined with GPS technology, requiring minimal worker input, is proposed. The requirements and approaches needed to utilize the system for locating precast concrete components with minimal worker input in the storage yard of a manufacturing plant were developed.”

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GPS - GIS

Application of integrated GPS and GIS technology for reducing construction waste and improving construction efficiency (2004) Heng Li, Hong Kong Polytechnic University, Zhen Chen, Massey University, Liang Yong, Hong Kong Polytechnic University and Stephen C.W. Kong, Loughborough University

“…the integrated GPS and GIS technology is combined to the M&E system based on the Wide Area Network (WAN).”

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Radio Frequency Identification (RFID)

Tracking the Location of Materials on Construction Projects, (2005) Jong-Chul Song, University of Texas at AustinThesis on the viability to use RFID devises in the field. The devises were utilized as a tracking and location devise. In the final evaluation an accuracy level of 4 meters demonstrated.

A Framework for Real-Time Construction Project Progress Tracking, (2006) A. G. Ghanem and Y. A. AbdelRazig Florida State University

“…automated system of reading RFID tags placed on items that send out either a tracking number, or other information for that item, directly to the reader. Keeping track of the material used on site, based on the estimated quantity will permit making a better estimate of the amount of work done on a construction site.”

Presented at: 10th Biennial International Conference on Engineering, Construction, and Operations in Challenging Environments (Earth & Space 2006)

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Haul Truck Onboard Sensors• RFID

– Transmitter• Quarry load out transceiver • GPS

– Data logger– 802.11b Wireless LAN

• MEM– Accelerometer / pressure

transducer

• Central Server Receiver– Cellular Transmitter

Record of truck location, bed tilt time & truck identificationRecord of material type and weight from quarry transmission.Data received by central on site receiver, retransmitted in batch by cellular transmitter to central server.

Source: sparkfun.com



Source: http://www.engeniustech.com/datacom/products/details.aspx?id=174

transmit static

identification data

record location

data

transmit recorded data

Bridge/Repeater

Sense tilt & loadtransmit data to server

transmit quarry data

http://www.engeniustech.com/img/Products/prodImg174.jpg

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Field Tablet PCDistribute to field staff

– Electronic timecards & foreman report– Communication– Safety– Searchable plans & specifications– Object based (BIM) information– Location based schedule– View 4D schedule– Wi-Fi / cellular link w/ central server– Rugged solid state memory– Embedded sensors i.e. RFID reader, GPS

http://www.airforce-technology.com

http://www.massgroup.com

“Framework for Providing Customized Data Representations for Effective and Efficient Interaction with Mobile Computing Solutions on Construction Sites”, J. Reinhardt, J. Garrett Jr., and B. Akinci 2005

http://www.trimble.com

http://www.samsung.com



http://www.airforce-technology.com/contractors/software/rave2/rave23.html

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4D Schedule

A 4D schedule updated throughout the project duration could be used as an as-built, useful to maintenance personnel throughout the lifecycle of infrastructure.

Scenario:

On day 115, change order results in additional electrical wiring and revised plumbing. Updated 4-D schedule records these changes while current and results in dynamic as-built.

Image borrowed from: Product Model 4D--Construction Pilot, Calvin Kam, http://www.stanford.edu/group/4D/projects/calvin/PM4D.shtml

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Human SensoryHuman sensory (similar in use as sensor): • 2.1 Sight (object recognition)• 2.2 Hearing (RFID radio signal)• 2.3 Taste (material identification)• 2.4 Smell• 2.5 Touch (on-board sensory)• 2.6 Balance and acceleration • 2.7 Temperature • 2.8 Kinesthetic sense (clash detection)• 2.9 Pain • 2.10 Direction (GPS)• Weight relative to resistive effort, this is heavier than that and similar to

past experience weight of.The point is that the mechanical sensors are replications of the current sensor-

based measuring tool, the human. See F. Peterson ENGR thesis draft (http://stanford.edu/~granite/index.html) for a discussion of these human-based sensory methods.

Included in the ENGR thesis draft is a discussion of inherent limitations of human-based sensory, such as the risk of optical illusions in sight, and the accuracy of sight-based observational estimates of count, area, and volume quantities.

http://en.wikipedia.org/wiki/Sense#Sight

http://en.wikipedia.org/wiki/Sense#Hearing

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Process outputinput

PLCOSIS SOFT

JD Edwards

SAP

sensor sensor

Control module

Control module

Programmable Logic Controller (PLC)

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Social / Legal IssueBasic assumption in automated tracking systems is

unhindered data sharing and access to site

Reiteration of some commonly held concerns with data sharing

• Data sharing could divulge embarrassing mistakes in design / estimate

• Shortcuts taken by designer / estimator more apparent• Liability for modifications made after transfer of data

Observed on Stanford Y2&E2 project: all electronic drawings are transferred as .PDF files

Common practice: estimators will not pass on electronic version of estimate documents

Documents

1 Automated Data Collection Technology Automated Quantities Reporting Spring 2008 Forest Peterson – Stanford Construction Engineering & Management