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dc.contributor.authorShahi, Arash
dc.date.accessioned2012-03-09 19:29:41 (GMT)
dc.date.available2012-03-09 19:29:41 (GMT)
dc.date.issued2012-03-09T19:29:41Z
dc.date.submitted2012-03-05
dc.identifier.urihttp://hdl.handle.net/10012/6582
dc.description.abstractIn recent years, many researchers have investigated automated progress tracking for construction projects. These efforts range from 2D photo-feature extraction to 3D laser scanners and radio frequency identification (RFID) tags. A multi-sensor data fusion model that utilizes multiple sources of information would provide a better alternative than a single-source model for tracking project progress. However, many existing fusion models are based on data fusion at the sensor and object levels and are therefore incapable of capturing critical information regarding a number of activities and processes on a construction site, particularly those related to non-structural trades such as welding, inspection, and installation activities. In this research, a workflow based data fusion framework is developed for construction progress, quality and productivity assessment. The developed model is based on tracking construction activities as well as objects, in contrast to the existing sensor-based models that are focussed on tracking objects. Data sources include high frequency automated technologies including 3D imaging and ultra-wide band (UWB) positioning. Foreman reports, schedule information, and other data sources are included as well. Data fusion and management process workflow implementation via a distributed computing network and archiving using a cloud-based architecture are both illustrated. Validation was achieved using a detailed laboratory experimental program as well as an extensive field implementation project. The field implementation was conducted using five months of data acquired on the University of Waterloo Engineering VI construction project, yielding promising results. The data fusion processes of this research provide more accurate and more reliable progress and earned value estimates for construction project activities, while the developed data management processes enable the secure sharing and management of construction research data with the construction industry stakeholders as well as with researchers from other institutions.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectConstruction Managementen
dc.subjectData Fusionen
dc.subjectProgress Trackingen
dc.subjectActivity Trackingen
dc.subjectField Implementationen
dc.subjectUltra Wide Band (UWB)en
dc.subject3D Laser Scannersen
dc.titleActivity-Based Data Fusion for the Automated Progress Tracking of Construction Projectsen
dc.typeDoctoral Thesisen
dc.comment.hiddenI have made the revisions that were required, as noted below. I would very much appreciate it if you could please get back to me today, because I would like to send it for printing. The next printing pick-up is tomorrow! 1. The .pdf file name must appear as 'Shahi_Arash'. 2. Title page - the line that appears as 'Civil and Environmental Engineering' must be revised to appear as 'Civil Engineering'. 3. Chapter 1 Introduction - must appear as page 1.en
dc.pendingfalseen
dc.subject.programCivil Engineeringen
uws-etd.degree.departmentCivil and Environmental Engineeringen
uws-etd.degreeDoctor of Philosophyen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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