Due to the increasing complexity of buildings, the importance of proactive evacuation guidance that reflects real-time fire situations is increasing. In this paper, we designed and implemented a real-time fire situation recognition and intelligent evacuation route guidance system by combining IoT sensor networks and graph models. The proposed system instantly identifies fire locations from sensor nodes and dynamically generates routes that avoid dangerous areas using an optimal routing algorithm. For quantitative evaluation of the system, fire rate, path cost, and detour factor were defined as performance indicators. Simulation results demonstrated an optimal route with an evacuation distance of 45 m in a dynamic environment with a fire occurrence rate of 11.4%. Specifically, maintaining a detour factor of 0.20 demonstrated an effective balance between risk avoidance and evacuation speed. Furthermore, real-time evacuation efficiency analysis visualized the correlation between node status changes and evacuation distance over time, ensuring system reliability. This study is expected to be useful as an intelligent safety platform that maximizes evacuation efficiency and minimizes casualties in the event of a fire.
Jeong et al. (Thu,) studied this question.