基于大数据的实时人流量统计与预警系统的设计与实现

Design and Implementation of Real-Time Human Traffic Statistics and Early Warning System based on Big Data

目前,对于城市区域人流量统计预警的实现方法主要是视频监控与分析,但是视频监控设备覆盖范围的局限性大,无法保证人流数量统计的准确性。随着移动终端逐渐普及,利用移动终端的实时分布统计区域人流量并进行预警成为研究热点。笔者利用Kafka+Storm构建实时数据流处理系统,掌握移动终端的实时分布情况,完成了人流量统计和预警系统的架构设计、数据流设计以及关键算法的实现,最终通过浏览器对统计和预警结果进行展示。

At present,the main method to realize the statistical warning of human flow in urban areas is video monitoring and analysis,but the coverage scope of video monitoring equipment is limited,and the accuracy of the statistical analysis of human flow cannot be guaranteed.With the rapid rise of the penetration rate of mobile terminals,the use of real-time distribution of mobile terminals to statistical regional traffic and early warning has become a research hotspot.This paper uses Kafka+Storm to build a realtime data flow processing system,master the real-time distribution of mobile terminals,complete the architecture design,data flow design and realization of key algorithms of the human traffic statistics and early warning system,and finally display the statistics and early warning results through the browser.