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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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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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Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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
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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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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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
Automated Quantities ReportingAutumn 2007
Forest Peterson – Stanford CEM
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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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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”
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
http://www.cat.com/cda/files/191058/7/AEHQ5549.pdf
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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
Automated Quantities ReportingAutumn 2007
Forest Peterson – Stanford CEM
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
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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
Automated Quantities ReportingSpring 2008
Forest Peterson – Stanford Construction Engineering & Management
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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.
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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