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Automated Site Data Acquisition for Effective Project Control

Title:

Automated Site Data Acquisition for Effective Project Control

Montaser, Ali (2013) Automated Site Data Acquisition for Effective Project Control. PhD thesis, Concordia University.

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Abstract

Tracking and control of construction projects depend primarily on the accuracy,
frequency and time required to collect actual onsite data of construction operations that
characterize the work progress. Earned Value Analysis (EVA) is being used for reporting work
progress and for forecasting project status at completion and at any future time horizon. Critical
to its reliable application is accurate and timely data for quantifying the budgeted cost of work
performed. Automated site data acquisition has received considerable attention in recent years
to circumvent the limitations of manual data collection. The limitations of existing models lie
in their inability to measure the progress of different types of construction activities from
inception to completion in near real-time.
The objective of this research is to study and analyze the characteristics of automated
data acquisition technologies in construction. This thesis is carried out with a focus on
automating the process of data collection and project control. An automated model is developed
that integrates project visualization-information aspects, automated site data acquisition and
earned value analysis. The developed model consists of two main frameworks; one is for data
acquisition and the other for data analysis and processing. Data acquisition is carried out using
the integrated automated data acquisition technologies embedded in the tablet PC used in this
research as well as others, referred to here as independent, automated data acquisition
technologies. The developed model makes full use of 4D BIM to provide visualization and
pertinent information of activities in progress. The developed model embraces the human
factors to augment the visualization-information aspects, localization technologies and
development of progress templates. The developed model demonstrated the significance of
data fusion of a wide range of automated site data acquisition technologies and
visualization-information technologies.
A prime focus is placed on extensive field studies and experimental work. Field studies
on construction jobsite are conducted utilizing a wide range of technologies such as 3D
Scanner, RFID and GPS. Extensive experimental work is conducted to develop deployment
protocols for utilization of Ultra High Frequency (UHF) passive RFID in localization and
material tracking. The field and lab work resulted in a number of observations, findings, and
lessons learned for deployment of passive RFID in construction. The results presented in this
study demonstrate the potential use of short range RFIDs in location estimation and material
tracking in a cost-effective manner for indoor construction operations. The developed method
for location identification and material tracking using RFID technology can be used to obtain
information required for scalable, near-real-time decision-making and timely tracking of
project status.
The developed methods and algorithms are implemented in prototype software. It
consists of two computational frameworks; BIM+ and Control+. BIM+ is Two-Tier software,
which utilizes an object-oriented BIM model. So, it can be used as an advanced tool for data
acquisition through the user’s tablet PC. Control+ is Three-Tier Web-Based software for
processing the captured data from the tablet PC and independent automated data acquisition
technologies. The developed model, methods, algorithms and software constitute a step
ahead of current progress reporting applications and expand upon automated site data
acquisition technologies and visualization-information technologies use in construction.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Montaser, Ali
Institution:Concordia University
Degree Name:Ph. D.
Program:Building Engineering
Date:December 2013
ID Code:978609
Deposited By: ALI IBRAHIM
Deposited On:16 Jun 2014 13:27
Last Modified:18 Jan 2018 17:47
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