Automated quantification of construction workers’ exposure to struck-by falling object hazards

Abstract

The construction industry is among the most hazardous industries, and its continuously changing and complex environment results in a labour-intensive task to plan and prevent hazards. The current manual safety planning procedures cannot keep up with the construction progress. This leads to unplanned durations and an increased responsibility for the individual workers to analyse and act accordingly to an emerging situation. This work proposes an automated approach to identify and measure the amount of struck-by falling objects hazard exposure to the construction tasks and their assigned work crews. Additionally, falling objects can originate from activities not foreseen or planned due to planning resolution (e.g., crane lift paths or temporary impassable access routes). Therefore, it is investigated how to extend the current practises of safety analysis in both the planning and construction stages using BIM artificial intelligence and sensor techniques. The proposed strategy is to identify hazard sources and subjects based on their topology and nature in a spatiotemporal analysis. The proposed combinatorial analysis approach is validated in the case study performed on a real construction project in Finland. It yields new insights, which can be necessary for construction sequence decisions and convince workers to improve their safety behaviour.