A personalized Human Factors Analysis and Classification System (HFACS) for construction safety managementbased on context-aware technology
Ning Tang, Hao Hu, Feng Xu, Justin K. W. Yeoh, David Kim Huat Chua, Zhe Hu
Abstract
Human-related errors are the major causes of most accidents in construction industry, and Human Factors Analysis and Classification System (HFACS) is widely used to analyze and prevent these accidents. However, traditional HFACS models are usually conducted post-accident and neglect personalized accident causal factors that reflect the safety state of individuals more directly and varies in near real time. In this study, an improved HFACS model for personalized safety management is developed from literature research and expert experience and preliminary results show that the model is superior to traditional safety management by reflecting and analyzing the personalized safety state of workers.