Haolong Liu, Jingpeng Li, Yun-Shang Wang, Ruei-Yuan Wang
{"title":"Fire Risk Assessment and Emergency Route Decision Analysis Based on Big Data Platform—Example of Huizhou","authors":"Haolong Liu, Jingpeng Li, Yun-Shang Wang, Ruei-Yuan Wang","doi":"10.22161/ijaers.1010.7","DOIUrl":null,"url":null,"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.","PeriodicalId":13758,"journal":{"name":"International Journal of Advanced Engineering Research and Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced Engineering Research and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22161/ijaers.1010.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.