In recent years, one of the biggest challenges that the construction industry has struggled with is safety. Because of inadequately performed data collection and safety management process, evaluations of safety performance on a project are conducted mostly at the process or project level, not the individual level. The main objective of this dissertation is to develop a framework and methods for automate on-site data collection and safety performance evaluation of individual workers. It introduces two tracking-methodological developments and a method for assessing the safety performance of workers using tracking data. To this end, the study presents an integrated system of safety assessment that 1) uses the developed tracking system to automatically collect individual contextual data from the site, 2) analyzes these data together with pre-identified hazard data, and 3) evaluates the safety performance of individual workers. The scope of the work is limited to zone-based hazardous situations. It does not include hazards to workers while they are on the job (e.g., cutting fingers, falling from a ladder, equipment operation mistakes, electrocution). The findings of the study contribute to the body of knowledge in several ways: The proposed algorithmic development shows an effective method for indoor tracking; the safety procedural developments bridge on-site data collection and safety analysis processes; and, the safety performance index data provide safety-related information on an unprecedented level that has not been available in the industry. Thus, by augmenting our knowledge and understanding of worker safety, the developed methods should be of value to both researchers and practitioners.
Dr. Yong K. Cho
Dr. John Taylor, Dr. Iris Tien, Dr. Patricio Vela (ECE), Dr. Changbum Ahn (University of Nebraska-Lincoln), Dr. Nipesh Pradhananga (Florida International University)