Ju Wang, Dingyi Fang, Xiaojiang Chen, Liqiong Chang, Zhanyong Tang, Tianzhang Xing, Chen Liu
{"title":"Poster: A Low Cost People Flow Monitoring System For Sensing The Potential Danger","authors":"Ju Wang, Dingyi Fang, Xiaojiang Chen, Liqiong Chang, Zhanyong Tang, Tianzhang Xing, Chen Liu","doi":"10.1145/2789168.2795169","DOIUrl":null,"url":null,"abstract":"For a long history, stampede is one of the high potential disaster when thousands of people gathered. Current monitoring systems, however, can only detect the presence of a small number of sparsely located targets, rather than to monitor the change of people flow where there are large number of dense crowd in the environment. This paper presents DanSen, a low-cost people flow monitoring system for sensing the potential danger using the existing wifi infrastructures. Inspired by the dynamic light scattering (DLS) theory, the designed DanSen calculates the correlations between the initial channel state information (CSI) data and all the history CSI data to monitor the changes of people flow and also estimates the sharpness of the changes. By doing so, DanSen can be utilised to perceive the potential danger. Real-world experimental results illustrate the advantage and effectiveness of DanSen.","PeriodicalId":424497,"journal":{"name":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st Annual International Conference on Mobile Computing and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2789168.2795169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
For a long history, stampede is one of the high potential disaster when thousands of people gathered. Current monitoring systems, however, can only detect the presence of a small number of sparsely located targets, rather than to monitor the change of people flow where there are large number of dense crowd in the environment. This paper presents DanSen, a low-cost people flow monitoring system for sensing the potential danger using the existing wifi infrastructures. Inspired by the dynamic light scattering (DLS) theory, the designed DanSen calculates the correlations between the initial channel state information (CSI) data and all the history CSI data to monitor the changes of people flow and also estimates the sharpness of the changes. By doing so, DanSen can be utilised to perceive the potential danger. Real-world experimental results illustrate the advantage and effectiveness of DanSen.