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  1. 研究報告
  2. モバイルコンピューティングと新社会システム(MBL)
  3. 2016
  4. 2016-MBL-080

Train Route Detection with using Sensor Data and GIS

https://ipsj.ixsq.nii.ac.jp/records/174281
https://ipsj.ixsq.nii.ac.jp/records/174281
ebf8f946-7975-4e70-b91e-87a54bc69657
名前 / ファイル ライセンス アクション
IPSJ-MBL16080016.pdf IPSJ-MBL16080016.pdf (1.1 MB)
Copyright (c) 2016 by the Information Processing Society of Japan
オープンアクセス
Item type SIG Technical Reports(1)
公開日 2016-08-17
タイトル
タイトル Train Route Detection with using Sensor Data and GIS
タイトル
言語 en
タイトル Train Route Detection with using Sensor Data and GIS
言語
言語 eng
キーワード
主題Scheme Other
主題 位置情報と交通システム
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_18gh
資源タイプ technical report
著者所属
IBM Research - Tokyo
著者所属(英)
en
IBM Research - Tokyo
著者名 Masaki, Ono

× Masaki, Ono

Masaki, Ono

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著者名(英) Masaki, Ono

× Masaki, Ono

en Masaki, Ono

Search repository
論文抄録
内容記述タイプ Other
内容記述 Smart phones have many sensors (GPS/pedometer), so data can easily be obtained to estimate a user's context, which is an important factor for smart phone applications. In this paper, we present a method to detect past train routes (a sequence of stations) from GPS records using station location information. Although GPS sensors do not work well underground or in overcrowded areas, we solve this problem by thinking through all possible paths and weighting them using sensor records. To evaluate our method, we conducted an experiment with sensor data created by several people over more than two weeks and found that its accuracy exceeded the baseline accuracy.
論文抄録(英)
内容記述タイプ Other
内容記述 Smart phones have many sensors (GPS/pedometer), so data can easily be obtained to estimate a user's context, which is an important factor for smart phone applications. In this paper, we present a method to detect past train routes (a sequence of stations) from GPS records using station location information. Although GPS sensors do not work well underground or in overcrowded areas, we solve this problem by thinking through all possible paths and weighting them using sensor records. To evaluate our method, we conducted an experiment with sensor data created by several people over more than two weeks and found that its accuracy exceeded the baseline accuracy.
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AA11851388
書誌情報 研究報告モバイルコンピューティングとパーベイシブシステム(MBL)

巻 2016-MBL-80, 号 16, p. 1-6, 発行日 2016-08-17
ISSN
収録物識別子タイプ ISSN
収録物識別子 2188-8817
Notice
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
出版者
言語 ja
出版者 情報処理学会
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