Effective construction management involves real-time decisions regarding the progress of specific activities, the location of materials and equipment, and the construction site safety. The decision making process can be improved using real-time positioning technologies such as Radio Frequency Identification Device (RFID) systems, Global Positioning System (GPS), and Ultra Wide Band (UWB) sensors. While the GPS is not applicable to indoor positioning and RFID tags cannot provide a fully automated system for position location, the characteristics of UWB systems make this technology a strong candidate for a fully automated positioning system in an indoor construction environment. This thesis presents a comprehensive study of the performance of UWB systems in a controlled laboratory environment and in an institutional construction site in Waterloo, Canada as well as for a particular safety application. A primary objective of the research was to establish the accuracy of real-time position location under various conditions, including the effect of different construction materials (e.g., wood and metal), and to analyze changes in the accuracy of position location as construction progresses and the indoor environment physically evolves. Different challenges faced in implementing such a system in an active construction environment are addressed. Based on a statistical analysis of laboratory data, and considering the construction site experience, the reliability of the UWB positioning system for the aforementioned environments is discussed. Furthermore, an automated safety system is proposed using the real-time UWB positioning technology. Based on the error modeling of the UWB position location, an optimum alarming algorithm is designed for the proposed safety system and the reliability of such system is evaluated through a statistical analysis.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/5883 |
| Date | January 2011 |
| Creators | Aryan, Afrooz |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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