Fire Risk Assessment and Emergency Route Decision Analysis Based on Big Data Platform—Example of Huizhou

Haolong Liu, Jingpeng Li, Yun-Shang Wang, Ruei-Yuan Wang
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Abstract

With the process of urbanization, the frequency of fires is gradually increasing, and fire emergency work has become particularly important. This paper takes Huizhou City as an example and conducts a fire risk assessment based on the various conditions of the city using the Gaode big data platform. The analysis shows that the low-risk area within the Fourth Ring Road in Huicheng District is about 91.8%, the medium-risk area is about 6.72%, the secondary high-risk area is about 1.16%, and the high-risk area is about 0.31%. Meanwhile, we use Python code to calculate the decision analysis plan for fire emergency route selection. By collecting data on fire site locations, fire stations, and hospitals, combined with dynamic information such as road conditions and traffic flow, and utilizing the functions of the Gaode big data platform, route calculation and optimal path selection are carried out. This method will improve the efficiency of fire emergency response, reduce rescue time, and provide better assistance to the affected population.
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基于大数据平台的火灾风险评估与应急路径决策分析——以惠州市为例
随着城市化的进程,火灾发生的频率逐渐增加,火灾应急工作变得尤为重要。本文以惠州市为例,利用高德大数据平台,根据惠州市的各种情况进行火灾风险评估。分析表明,惠城区四环内低风险区约占91.8%,中风险区约占6.72%,次高风险区约占1.16%,高风险区约占0.31%。同时,使用Python代码计算火灾应急路径选择的决策分析方案。通过采集火场位置、消防站、医院等数据,结合道路状况、交通流量等动态信息,利用高德大数据平台的功能,进行路线计算和最优路径选择。这种方法将提高火灾应急响应的效率,缩短救援时间,并为受灾群众提供更好的援助。
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