Smart Safety: Big Data–Enabled System for Analysis and Management of Unsafe Behavior by Construction Workers
Qi Fang, Daniel Castro‐Lacouture, Chengqian Li
Abstract
In the era of big data, the extraction of valuable knowledge and insights becomes feasible through efficient data processing methods. In this research, we establish an analytical framework enabled by big data to aid in the management of construction workers’ unsafe behaviors. To evaluate workers’ behavioral patterns, a multistage data processing model is employed, uncovering previously unknown connections between unsafe act records and situational data. Leveraging the high-level knowledge derived from this analysis, personalized safety management strategies are formulated based on individual workers’ behavioral patterns. The effectiveness of the proposed framework is evaluated by comparing it to conventional management strategies across three construction sites. Results demonstrate that behavioral patterns discovered by the big data framework provide an important decision basis and achieve smart construction unsafe behavior management.