{"title":"基于校园无线网络日志的校园人群密度实时监控分析算法","authors":"Ying Xia, Shuping Wu, Hui-qun Yu","doi":"10.1117/12.2679233","DOIUrl":null,"url":null,"abstract":"In order to implement precision management on the campus, the decisions need data support, and the crowd density on campus is one of the important parts. Based on campus wireless network logs, which is widely used on the campus, this paper proposes an analysis algorithm to obtain online wireless network user numbers in real time and draws the conclusion that the numbers of online users can represent crowd density on campus. Experimental results show that this algorithm can effectively get the numbers of online users in each area of the campus, and the campus heat map made with these data can reflect the real-time distribution of campus crowd and crowd density. This method uses log analysis method which is a general solution for some problems and has practical value for in-depth analysis.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An analysis algorithm for real-time monitoring of campus crowd density based on campus wireless network logs\",\"authors\":\"Ying Xia, Shuping Wu, Hui-qun Yu\",\"doi\":\"10.1117/12.2679233\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to implement precision management on the campus, the decisions need data support, and the crowd density on campus is one of the important parts. Based on campus wireless network logs, which is widely used on the campus, this paper proposes an analysis algorithm to obtain online wireless network user numbers in real time and draws the conclusion that the numbers of online users can represent crowd density on campus. Experimental results show that this algorithm can effectively get the numbers of online users in each area of the campus, and the campus heat map made with these data can reflect the real-time distribution of campus crowd and crowd density. This method uses log analysis method which is a general solution for some problems and has practical value for in-depth analysis.\",\"PeriodicalId\":342847,\"journal\":{\"name\":\"International Conference on Algorithms, Microchips and Network Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Algorithms, Microchips and Network Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2679233\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Algorithms, Microchips and Network Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2679233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An analysis algorithm for real-time monitoring of campus crowd density based on campus wireless network logs
In order to implement precision management on the campus, the decisions need data support, and the crowd density on campus is one of the important parts. Based on campus wireless network logs, which is widely used on the campus, this paper proposes an analysis algorithm to obtain online wireless network user numbers in real time and draws the conclusion that the numbers of online users can represent crowd density on campus. Experimental results show that this algorithm can effectively get the numbers of online users in each area of the campus, and the campus heat map made with these data can reflect the real-time distribution of campus crowd and crowd density. This method uses log analysis method which is a general solution for some problems and has practical value for in-depth analysis.