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中国科学院大学学报 ›› 2015, Vol. 32 ›› Issue (3): 428-431.DOI: 10.7523/j.issn.2095-6134.2015.03.021

• 简报 • 上一篇    

基于大数据的热点区域人员流量实时监测系统

宋瑞1,2, 姚郑1   

  1. 1. 中国科学院大学, 北京 100049;
    2. 太极计算机股份有限公司, 北京 100091
  • 收稿日期:2014-03-21 修回日期:2014-07-29 发布日期:2015-05-15
  • 通讯作者: 宋瑞
  • 基金资助:

    国家科技重大专项(2010ZX03006-001-02)资助

Big data-based hot-spot real-time traffic monitoring system

SONG Rui1,2, YAO Zheng1   

  1. 1. University of Chinese Academy of Sciences, Beijing 100049, China;
    2. Taiji Computer Corporation Limited, Beijing 100091, China
  • Received:2014-03-21 Revised:2014-07-29 Published:2015-05-15

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.

关键词: 人员流量监测, 大数据, 实时计算, 微云网络

Abstract:

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.

Key words: traffic monitoring, big data, real-time processing, micro cloud network

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