IoT-Enabled Multi-Agent Simulation for Hazard Detection and Safety in Construction

Construction sites are inherently hazardous environments, often prone to accidents that compromise worker safety and disrupt operational efficiency. Despite advancements in safety protocols, the dynamic nature of these sites necessitates innovative solutions to proactively mitigate risks. The goal of this study is to investigate the integration of Internet of Things (IoT)-enabled knowledge sharing within a multi-agent simulation framework to enhance hazard detection and worker safety. The proposed system models construction sites as dynamic environments where agents represent workers, tasks, and hazards. By leveraging IoT technology, agents can share hazard information in real-time, reducing the need for direct hazard encounters and potentially optimizing task efficiency. Implemented using the Tropos methodology and NetLogo, the simulation compares scenarios with and without IoT support, analyzing task completion rates, hazard interactions, and navigation patterns. Results show that IoT-enabled knowledge sharing improves hazard avoidance, boosts task efficiency, and supports safer navigation. Expert feedback validates the model’s alignment with real-world practices and suggests refinements such as predefined pathways and dynamic hazard representation. This study highlights how integrating IoT within multi-agent systems can enhance construction site safety and productivity.