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Automating Analysis of Construction Workers Viewing Patterns for Personalized Safety Training and Management

Authors :
Jeelani, Idris
Han, Kevin
Albert, Alex
Publication Year :
2018

Abstract

Unrecognized hazards increase the likelihood of workplace fatalities and injuries substantially. However, recent research has demonstrated that a large proportion of hazards remain unrecognized in dynamic construction environments. Recent studies have suggested a strong correlation between viewing patterns of workers and their hazard recognition performance. Hence, it is important to study and analyze the viewing patterns of workers to gain a better understanding of their hazard recognition performance. The objective of this exploratory research is to explore hazard recognition as a visual search process to identifying various visual search factors that affect the process of hazard recognition. Further, the study also proposes a framework to develop a vision based tool capable of recording and analyzing viewing patterns of construction workers and generate feedback for personalized training and proactive safety management.<br />Comment: ISARC 2018 Submission

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1809.00949
Document Type :
Working Paper