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- W150913364 abstract "Construction sites are well known for their dynamic and challenging nature. Several researchers are investigating the application of various Real-time Location Systems (RTLSs) for improving the safety and productivity of construction projects. When integrated with real-time data analysis systems, RTLS can contribute to make the construction environment smarter and safer by identifying safety hazards and inefficient resource configurations. Previous research shows that the Ultra-Wideband (UWB) technology, an emerging type of RTLS, is suitable for the identification and tracking of construction resources. However, a thorough study to evaluate the impact of the factors that affect the performance of the UWB RTLS in construction projects is still required. This research investigates the performance of UWB RTLSs in indoor and outdoor environments along with the evaluation of the factors which affect their performance. Moreover, the harsh environment of construction sites and the complex nature of construction projects provide numerous challenges for an individual technology to deliver accurate information in a timely manner. Therefore, this research also proposes a Multi-Sensor Data Fusion (MSDF) approach which leverages the benefits of video recording and image processing as a complimentary data source. It was found that the UWB RTLS is an effective tool to monitor construction resources; however, some of the UWB data can be missing or erroneous and the quality of the data can be improved by applying a suitable data enhancement method to accurately localize construction equipment. Furthermore, it was noted that the MSDF approach has the potential to better localize construction equipment by overcoming the limitations of UWB RTLS." @default.
- W150913364 created "2016-06-24" @default.
- W150913364 creator A5076713902 @default.
- W150913364 date "2014-09-11" @default.
- W150913364 modified "2023-09-24" @default.
- W150913364 title "UWB RTLS for Construction Equipment Localization: Experimental Performance Analysis and Fusion with Video Data" @default.
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