Thanchanok Sutjarittham, Hassan Habibi Gharakheili, S. Kanhere, V. Sivaraman
{"title":"Demo Abstract: A Tool to Access and Visualize Classroom Attendance Data from a Smart Campus","authors":"Thanchanok Sutjarittham, Hassan Habibi Gharakheili, S. Kanhere, V. Sivaraman","doi":"10.1109/ipsn.2018.00033","DOIUrl":null,"url":null,"abstract":"This demo presents our web-tool to access and visualize student attendance data obtained from instrumenting a pilot set of classrooms with people counting sensors in a large university campus in Sydney, Australia. We showcase two aspects: (1) how to access and process our open data-set containing time-stamped occupancy counts for 9 lecture rooms of varying size in which over 250 courses are conducted over a 12-week semester; and (2) visualizing occupancy at multiple spatial (per-room and per-course) and temporal (over a day, week, or semester) granularities, enabling new insights into student attendance and room usage patterns.","PeriodicalId":358074,"journal":{"name":"2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ipsn.2018.00033","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
This demo presents our web-tool to access and visualize student attendance data obtained from instrumenting a pilot set of classrooms with people counting sensors in a large university campus in Sydney, Australia. We showcase two aspects: (1) how to access and process our open data-set containing time-stamped occupancy counts for 9 lecture rooms of varying size in which over 250 courses are conducted over a 12-week semester; and (2) visualizing occupancy at multiple spatial (per-room and per-course) and temporal (over a day, week, or semester) granularities, enabling new insights into student attendance and room usage patterns.