Construction Research Congress 2020
Improving Safety Performance in Construction Using Eye-Tracking, Visual Data Analytics, and Virtual Reality
Publication: Construction Research Congress 2020: Safety, Workforce, and Education
ABSTRACT
Globally, construction is among the most dangerous industries. Among others, research has demonstrated that construction workers and professionals fail to recognize and manage an unacceptable number of safety hazards. To address this, past research has focused on examining several factors including training, education, and management support that may indirectly influence hazard identification and management performance. However, proximal factors associated with poor hazard identification and management at the work interface has received very little attention. This paper summarizes our research aimed at (1) understanding why workers fail to identify and manage safety hazards as they participate in hazard recognition and management efforts and; (2) developing evidence-based interventions to counter poor hazard identification and management performance in the construction industry. This includes examining hazard recognition as a visual search task and understanding how search pattern (i.e., how workers examine the work environment) affects hazard recognition performance. More specifically, the research used eye-tracking technology to examine the relationship between how workers examine the workplace and the resulting hazard identification performance. Based on this new knowledge generated, new interventions were developed to improve hazard recognition and management performance. These include two interventions. First, an immersive hyper-realistic mixed reality training environment that was developed using stereoscopic visual data captured from real construction workplaces. The testing of the intervention with 56 participants suggested that the intervention can significantly improve hazard identification and management performance. Second, an AI-based system that detects hazardous conditions and objects in real-time to assist workers and managers. The system uses the live video captured by a wearable camera to localize the workers on a pre-built global map, detect any hazard present around the worker, and warns them in real-time. The system is tested in indoor and outdoor construction environments, which indicate 93% accuracy in detecting workers’ proximity to hazards.
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Published In
Construction Research Congress 2020: Safety, Workforce, and Education
Pages: 395 - 404
Editors: Mounir El Asmar, Ph.D., Arizona State University, David Grau, Ph.D., Arizona State University, and Pingbo Tang, Ph.D., Arizona State University
ISBN (Online): 978-0-7844-8287-2
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Nov 9, 2020
Published in print: Nov 9, 2020
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