Crowd Density Estimation in Railway Stations

• Item type: Symposium_02(1)
• 公開日: 2016-10-12
• タイトル: Crowd Density Estimation in Railway Stations
• タイトル / 言語: en
• タイトル: Crowd Density Estimation in Railway Stations
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Congestion Estimation
• キーワード / 主題Scheme: Other
• キーワード / 主題: Train Station
• キーワード / 主題Scheme: Other
• キーワード / 主題: Smartphone
• キーワード / 主題Scheme: Other
• キーワード / 主題: Crowd Sensing
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Osaka University
• 著者所属: Osaka University
• 著者所属: Osaka University
• 著者所属: Osaka University
• 著者所属(英): en
• 著者所属(英): Osaka University
• 著者所属(英): en
• 著者所属(英): Osaka University
• 著者所属(英): en
• 著者所属(英): Osaka University
• 著者所属(英): en
• 著者所属(英): Osaka University
• 著者名: Elhamshary, Moustafa; Uchiyama, Akira; Yamaguchi, Hirozumi; Higashino, Teruo
• 著者名(英): Moustafa, Elhamshary; Akira, Uchiyama; Hirozumi, Yamaguchi; Teruo, Higashino
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: We present CrowdApp: a participatory system that leverages the crowd - sensed data collected from users’ phones during their train commutations to estimate the real - time crowd density in railway stations. CrowdApp continuously tracks the passenger’s position in the station as well as identifies his / her context (e.g., waiting for a train, etc). Finally, CrowdApp extracts novel features, based on the user’s location and context, from the phone sensors to identify the crowd density along the user route in railway stations. Evaluation of CrowdApp through a field experiment in eight train stations, shows that it can infer the crowd density e ciently highlighting its promise as a ubiquitous travel support service.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: We present CrowdApp: a participatory system that leverages the crowd - sensed data collected from users’ phones during their train commutations to estimate the real - time crowd density in railway stations. CrowdApp continuously tracks the passenger’s position in the station as well as identifies his / her context (e.g., waiting for a train, etc). Finally, CrowdApp extracts novel features, based on the user’s location and context, from the phone sensors to identify the crowd density along the user route in railway stations. Evaluation of CrowdApp through a field experiment in eight train stations, shows that it can infer the crowd density e ciently highlighting its promise as a ubiquitous travel support service.
• 書誌情報: 第24回マルチメディア通信と分散処理ワークショップ論文集; 巻 2016, p. 40-49, 発行日 2016-10-12
• 出版者 / 言語: ja
• 出版者: 情報処理学会