Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data

© 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...

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Main Authors: Adiporl Binthaisong, Jaruwan Srichan, Santi Phithakkitnukoon
格式: Conference Proceeding
出版: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/43642
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spelling th-cmuir.6653943832-436422018-04-25T07:20:24Z Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data Adiporl Binthaisong Jaruwan Srichan Santi Phithakkitnukoon Computer Science Agricultural and Biological Sciences © 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. 2018-01-24T03:51:13Z 2018-01-24T03:51:13Z 2017-09-11 Conference Proceeding 2-s2.0-85030859746 10.1145/3123024.3124413 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030859746&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/43642
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Agricultural and Biological Sciences
spellingShingle Computer Science
Agricultural and Biological Sciences
Adiporl Binthaisong
Jaruwan Srichan
Santi Phithakkitnukoon
Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
description © 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.
format Conference Proceeding
author Adiporl Binthaisong
Jaruwan Srichan
Santi Phithakkitnukoon
author_facet Adiporl Binthaisong
Jaruwan Srichan
Santi Phithakkitnukoon
author_sort Adiporl Binthaisong
title Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
title_short Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
title_full Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
title_fullStr Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
title_full_unstemmed Wi-Crowd: Sensing and visualizing crowd on campus using Wi-Fi access point data
title_sort wi-crowd: sensing and visualizing crowd on campus using wi-fi access point data
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030859746&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43642
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