A decision support framework for site safety monitoring using RFID and BIM

Sattineni, A

Abstract

Supervision of construction workers on a site is crucial to ensure construction worker safety, to maintain the quality of work performed and to maintain acceptable levels of productivity. The act of supervision itself requires the site superintendent to physically monitor workers in an environment that is constantly changing throughout the various phases of construction. This can be a complicated task on a medium to large building site with several trades working simultaneously on multiple floors or areas. There exists a need for construction superintendents to know the location of construction workers within a site. Academicians and industry professionals have demonstrated the use of Radio Frequency Identification (RFID) Tags in construction applications in the past few years. RFID tags have successfully been used to track construction materials, equipment and tools. Studies indicate that the use of RFID tags in construction improves the overall process of construction. Building information modeling (BIM) technology is emerging as the industry standard in the architecture, engineering and construction (AEC) sector. BIM is being used as a comprehensive design, management, visualization, communication and facility maintenance and management tool. This research presents the creation of a decision support framework for site supervision based on monitoring construction workers by combining RFID technology with BIM. A conceptual decision support framework to monitor site safety was developed by interviewing site superintendents. Conducting a web-based questionnaire of construction industry professionals validated the framework. A proof-of-concept virtual prototype was created to track the movement of construction workers using RFID and BIM. The procedures undertaken to create the conceptual framework and the virtual prototype are described in the thesis.

Citation

Sattineni, A. A decision support framework for site safety monitoring using RFID and BIM. (Thesis). University of Salford, College of Science and Technology

• Thesis Type: Thesis
• Deposit Date: Apr 9, 2015
• Publicly Available Date: Apr 9, 2015
• Award Date: Oct 8, 2014