A Smart Evacuation Guidance System for Large Buildings

Abstract

In large buildings, during the situation of fire or other hazards, a smart evacuation guidance system needs to fully consider manifold aspects of hazards to guide evacuees through exit gates as fast as possible by dynamic and safe routes. In this paper, we propose a smart evacuation guidance system with a dynamic evacuation routing approach by using the LCDT (Length-Capacity-Density-Trustiness) weighted graph model and partial view (PV) information which represents the hazard intensity and the crowd congestion information of a group of sections/floors in the building. The proposed system is designed as a distributed system with multiple layers of computing by using smart indicators. Given such a system, we develop an efficient distributed approach, so-called LCDT&PV, to find out effective evacuation routes dynamically. We then propose an estimating congestion strategy in order to improve the efficiency of dynamic evacuation routes. To validate the proposed system, we implement a simulator to compare the proposed evacuation routing approach with baseline approaches. Experimental results show that the proposed approach reduces up to 30% of the total evacuation time compared with others. Furthermore, through the results of initial smart indicator implementation, which can interact with the simulator, we show the viability of the proposed system.