摘要
针对地铁隧道监控系统存在的架构臃肿、灵活度低,传感器集成难,大吞吐数据传输延迟大,缺乏数据处理算法与信息挖掘模型问题,提出基于微服务、5G、人工智能的解决方法,建立了地铁隧道的多源异构传感器自动化监控系统。系统基于灵活、易扩展的架构实现,能够快速对多源异构传感器进行集成。同时,系统实现了监控视频等大吞吐数据的在线传输与存储,以及高通量实时监测数据的高级解算与信息挖掘,为全面、精准地监控地铁隧道结构变形提供了技术手段。
The existing subway tunnel monitoring system has the problems of bloated system structure with low flexibility,difficult sensor integration,large throughput data transmission delay,and lack of data processing algorithms and information mining models.To solve these problems,a solution based on microservices,5G and artificial intelligence has been proposed,and a multi-source heterogeneous sensor automatic monitoring system has been established.The system is implemented based on a flexible and easily expandable architecture,which can quickly integrate multi-source heterogeneous sensors.At the same time,the system realizes the online transmission and storage of high-throughput data such as surveillance video,as well as the advanced calculation and information mining of high-throughput real-time monitoring data,providing technical means for comprehensive and accurate monitoring of subway tunnel structural deformation.
作者
张姗姗
李家平
张明
ZHANG Shanshan;LI Jiaping;ZHANG Ming(SGIDI Engineering Consulting(Group)Co.,Ltd.,Shanghai 200093,China;Shanghai Metro Monitoring Management Co.,Ltd.,Shanghai 200070,China)
出处
《城市勘测》
2024年第3期59-63,共5页
Urban Geotechnical Investigation & Surveying
关键词
地铁隧道
微服务
多源异构传感器
自动化变形监控系统
subway tunnel
microservice
multi-source heterogeneous sensor
automatic deformation monitoring system
