Abstract
Fire hazard in public buildings may result in serious casualties due to the difficulty of evacuation caused by intricate interior space and unpredictable development of fire situations. It is essential to provide safe and reliable indoor navigation for people trapped in the fire. Distinguished from the global shortest rescue route planning, a framework focusing on the local safety performance is proposed for emergency evacuation navigation. Sufficiently utilizing the information from Building Information Modeling (BIM), this framework automatically constructs geometry network model (GNM) through Industry Foundation Classes (IFC) and integrates computer vision for indoor positioning. Considering the available local egress time (ALET), a back propagation (BP) neural network is applied for adjusting the rescue route according to the fire situation, improving the local safety performance of evacuation. A campus building is taken as an example for proving the feasibility of the framework proposed. The result indicates that the rescue route generated by proposed framework is secure and reasonable. The proposed framework provides an idea for using real-time images only to implement the automatic generation of rescue route when a fire hazard occurs, which is passive, cheap, and convenient.
Highlights
According to the report released by the Ministry of Emergency Management of China, 1045 people were killed by fire in residential and public buildings in 2019, accounting for 78.3% of the total fire fatalities [1], which clearly reveals the urgent need of reducing the fire hazards in public buildings [2,3]
Through a Building Information Modeling (BIM) model established according to the as-built drawings, an Industry Foundation Classes (IFC) model was generated and its class/relations extraction was implemented by IFC JAVA TOOLBOX toolkit [60]
IFC models can be exported by mainstream BIM software or by some independent IFC tools
Summary
According to the report released by the Ministry of Emergency Management of China, 1045 people were killed by fire in residential and public buildings in 2019, accounting for 78.3% of the total fire fatalities [1], which clearly reveals the urgent need of reducing the fire hazards in public buildings [2,3]. To offer guidelines for indoor evacuees in case of fire emergency, this paper presents a framework for generation of reliable rescue route, considering the safety performance of evacuation in fire scenario. For accurate indoor rescue routing, indoor positioning techniques are essential and have been extensively studied, including radio frequency identification, Bluetooth, wireless local area network (WLAN), and visible light [4,7,11]. These active indoor positioning techniques, which are relatively less reliable in a fire scenario, are relatively complex and expensive. It is worth noting that the safety performance of the rescue route is sometimes more significant than its simple distance under fire scenario [5,9]
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