摘要
在地震灾害应急救援中由于无法准确定位救援位置,导致救援速度比较慢,因此,研究基于智慧校园人脸识别的地震灾害应急救援方法,构建一个包含校园内所有人员的基础信息库,并安装相关人脸识别设施。地震灾害发生后,对设备采集信息进行识别,确定地震灾害中校园内被困人员数量以及被困人员最后出现区域(即被困区域),以建筑破坏指数表示地震灾害下校内建筑结构风险,将建筑结构风险由高至低划分为5个等级,结合智慧校园人脸识别、校内建筑结构风险等级以及路网模型,生成包含基础资料、校内复合灾害分析与应急救援要素规划等的地震灾害应急救援方案,根据救援方案完成救援力量的合理部署,再加上多种救援技术的应用,最终实现有效的地震灾害应急救援,并提出安全优先、安保优化等校园防震减灾规划策略。
In the earthquake disaster emergency rescue,the rescue speed is relatively slow due to the failure to accurately locate the rescue location.Therefore,we study the earthquake disaster emergency rescue method based on smart campus face recognition,construct a basic information database including all personnel in the campus,and installs relevant face recognition facilities.After the earthquake disaster,the information collected by the equipment is identified to determine the number of trapped people in the campus and the last area of the trapped people(i.e.the trapped area).The building damage index is used to represent the risk of the campus building structure under the earthquake disaster,and the building structure risk is divided into five levels from high to low According to the risk level of building structure and road network model,the earthquake disaster emergency rescue plan including basic data,campus composite disaster analysis and emergency rescue element planning is generated.According to the rescue plan,the reasonable deployment of rescue forces is completed.Combined with the application of a variety of rescue technologies,the effective earthquake disaster emergency rescue is finally realized,and the safety priority,emergency rescue and emergency rescue are put forward Security optimization and other campus earthquake prevention and disaster reduction planning strategies.
作者
张亮
徐力杰
ZHANG Liang;XU Lijie(Jiangsu Vocational Institute of Commerce,Nanjing 211168,China;Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
出处
《灾害学》
CSCD
北大核心
2021年第4期152-155,162,共5页
Journal of Catastrophology
基金
中国博士后科学基金资助项目(2016M601859)
江苏省博士后科研资助计划项目(1701047A)
江苏省社科联项目(2018SJA06345)
江苏经贸职业技术学院+重点项目(JSJM19021)。
关键词
智慧校园
人脸识别
地震灾害
应急救援
建筑风险等级
救援方案
smart campus
face recognition
earthquake disaster
emergency rescue
building risk level
rescue scheme
作者简介
第一作者:张亮(1983-),男,汉族,江苏宜兴人,硕士,工程师,主要从事计算机科学与技术、教育信息化研究.E-mail:yxrzl@163.com。
