Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity

• Item type: Journal(1)
• 公開日: 2019-01-15
• タイトル: Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity
• タイトル / 言語: en
• タイトル: Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：未来の暮らしを支えるパーベイシブシステムと高度交通システム] real-time Wi-Fi signal analysis, passenger information, public transportation, congestion, estimation
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Information Science and Engineering, Ritsumeikan University
• 著者所属: College of Information Science and Engineering, Ritsumeikan University
• 著者所属: College of Information Science and Engineering, Ritsumeikan University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Engineering, Ritsumeikan University
• 著者所属(英): en
• 著者所属(英): College of Information Science and Engineering, Ritsumeikan University
• 著者所属(英): en
• 著者所属(英): College of Information Science and Engineering, Ritsumeikan University
• 著者名: Thongtat, Oransirikul; Ian, Piumarta; Hideyuki, Takada
• 著者名(英): Thongtat, Oransirikul; Ian, Piumarta; Hideyuki, Takada
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Quality of service is one factor passengers consider when deciding to use the public transportation system. Increasing the quality of service can be done in several ways, such as improving on-time arrival, reducing waiting time, and providing seat availability information. We believe that if passengers have better information for making decisions, that can increase the quality of service. This paper proposes estimating the number of passengers by analyzing signals from their Wi-Fi devices, classifying them as originating from passenger or non-passenger devices using a real-time filtering mechanism. Experimental validation was performed aboard busses of different types taking different routes. Our experimental results show that filtered data can classify passenger device signals from environmental ones with an accuracy of 75 percent, which is a promising basis for providing real-time information to passengers that improves the quality of their service.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.27(2019) (online); DOI http://dx.doi.org/10.2197/ipsjjip.27.25; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Quality of service is one factor passengers consider when deciding to use the public transportation system. Increasing the quality of service can be done in several ways, such as improving on-time arrival, reducing waiting time, and providing seat availability information. We believe that if passengers have better information for making decisions, that can increase the quality of service. This paper proposes estimating the number of passengers by analyzing signals from their Wi-Fi devices, classifying them as originating from passenger or non-passenger devices using a real-time filtering mechanism. Experimental validation was performed aboard busses of different types taking different routes. Our experimental results show that filtered data can classify passenger device signals from environmental ones with an accuracy of 75 percent, which is a promising basis for providing real-time information to passengers that improves the quality of their service.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.27(2019) (online); DOI http://dx.doi.org/10.2197/ipsjjip.27.25; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 60, 号 1, 発行日 2019-01-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764