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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Adiporl Binthaisong | en_US |
dc.contributor.author | Jaruwan Srichan | en_US |
dc.contributor.author | Santi Phithakkitnukoon | en_US |
dc.date.accessioned | 2018-09-05T03:34:27Z | - |
dc.date.available | 2018-09-05T03:34:27Z | - |
dc.date.issued | 2017-09-11 | en_US |
dc.identifier.other | 2-s2.0-85030859746 | en_US |
dc.identifier.other | 10.1145/3123024.3124413 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030859746&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/57057 | - |
dc.description.abstract | © 2017 Association for Computing Machinery. This paper presents Wi-Crowd, a system for visualizing the crowd level based on Wi-Fi usage data on campus by presenting it on an interactive 3D graphics, including map rotation, zoom-in/out, and display selections. The system uses animation to display the dynamism of crowd on campus based on the internet usage behavior in different buildings and time periods. The sensed crowd level is comparable to the student registration information. This developed system can be used to sense the crowd level and can be beneficial to future studies in campus behavior or even city-level behavior, and management of internet usage and crowd on campus such as scheduling optimization, campus traffic management and planning. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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