Foot Traffic Analysis Using Wi-Fi Sensor During the Tokyo 2020 Olympics and Paralympics

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dc.contributor.authorTraganmaturapot, Peerada
dc.contributor.authorSonehara, Noboru
dc.contributor.authorHiruma, Nobuharu
dc.contributor.authorCooharojananone, Nagul
dc.contributor.authorJirapongwanich, Jirakit
dc.contributor.authorYodsakuntip, Kanat
dc.contributor.authorAtchariyachanvanich, Kanokwan
dc.date.accessioned2026-08-06T10:38:47Z
dc.date.available2026-08-06T10:38:47Z
dc.date.issued2023-01-01
dc.description.abstractVarious real-world factors, such as time, weather, distance, environment, the COVID-19 pandemic, or even protests, can all impact human decision-making. However, restrictions and unexpected occurrences may also influence people's decisions regarding their path at any given time. These factors can lead to challenges in managing foot traffic at largescale events. In response to these challenges, this paper proposes a data-driven web-based foot traffic management supporting dashboard for large-scale events based on limited pedestrian count data, consisting of sensor name, latitude, longitude, MAC address, Datetime, and RSSI, collected by Wi-Fi sensors around the Sendagaya area during the Tokyo 2020 Olympics and Paralympics. The results confirmed that our proposed web-based dashboard contributes to human behavior understanding and decision-supporting policymaking for foot traffic management, which improves the design of spectator movement between transportation and venues in large-scale events. Furthermore, the dashboard is valuable from various perspectives, including preventing crowd crushing, redesigning areas to increase engagement in the shopping district, and improving traffic management.
dc.identifier.citation7th International Conference on Information Technology Incit 2023, 424-429, 2023
dc.identifier.doi10.1109/InCIT60207.2023.10413175
dc.identifier.other2-s2.0-85185830900
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/13685
dc.source7th International Conference on Information Technology Incit 2023
dc.subjectbusiness intelligence
dc.subjectdata analysis
dc.subjectdata visualization
dc.subjectdata-driven
dc.subjectfoot traffic
dc.subjectIoT
dc.subjectpeople flow
dc.subjectTokyo 2020 Olympics and Paralympics
dc.subjecttransportation
dc.subjectWi-Fi sensors
dc.titleFoot Traffic Analysis Using Wi-Fi Sensor During the Tokyo 2020 Olympics and Paralympics
dc.typeConference Paper

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