摘要
采用大数据技术实现一个热点区域人员流量的实时监测系统.该系统分析热点区域内每个出入口实时人员流量,挖掘各热点区域驻留人员数量规律,从而科学地安排资源及运营管理.整个处理过程耗时少于15 s,误差小于7.5%.运营结果表明该系统达到了大数据的实时采集、实时分析处理和实时分区控制的可实用目标.
A big data-based hot-spot real-time traffic monitoring system is implemented. The system analyzes the passenger flow of each entry in real time, estimates the regular pattern of stay passengers in each hot-spot, and scientifically allocates resources for operation and administration. The period of the real-time processing in the system is shorter than 15 seconds, and the error rate of object detection is less than 7.5%. The operation results show that the system achieves the practical goals of real-time collection, analysis, and processing for big data.
出处
《中国科学院大学学报（中英文）》
CAS
CSCD
北大核心
2015年第3期428-431,共4页
Journal of University of Chinese Academy of Sciences
基金
国家科技重大专项(2010ZX03006-001-02)资助
关键词
人员流量监测
大数据
实时计算
微云网络
traffic monitoring
big data
real-time processing
micro cloud network
