{"id":193887,"updated":"2025-01-19T23:47:13.855894+00:00","links":{},"created":"2025-01-19T00:59:01.383472+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00193887","sets":["581:9633:9634"]},"path":["9634"],"owner":"44499","recid":"193887","title":["Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-01-15"},"_buckets":{"deposit":"d513f403-ffda-43e1-af6e-c174ace547a1"},"_deposit":{"id":"193887","pid":{"type":"depid","value":"193887","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity","author_link":["455241","455242","455243","455246","455245","455244"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity"},{"subitem_title":"Classifying Passenger and Non-passenger Signals in Public Transportation by Analysing Mobile Device Wi-Fi Activity","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[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","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2019-01-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Engineering, Ritsumeikan University"},{"subitem_text_value":"College of Information Science and Engineering, Ritsumeikan University"},{"subitem_text_value":"College of Information Science and Engineering, Ritsumeikan University"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Engineering, Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"College of Information Science and Engineering, Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"College of Information Science and Engineering, Ritsumeikan University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/193887/files/IPSJ-JNL6001012.pdf","label":"IPSJ-JNL6001012.pdf"},"date":[{"dateType":"Available","dateValue":"2021-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6001012.pdf","filesize":[{"value":"476.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a787b52e-2ea6-4309-a0a5-b1f8f6dec19b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Thongtat, Oransirikul"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ian, Piumarta"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideyuki, Takada"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Thongtat, Oransirikul","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ian, Piumarta","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideyuki, Takada","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"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. \n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.27(2019) (online)\nDOI　http://dx.doi.org/10.2197/ipsjjip.27.25\n------------------------------","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"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. \n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.27(2019) (online)\nDOI　http://dx.doi.org/10.2197/ipsjjip.27.25\n------------------------------","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2019-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"60"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}