A stayed location estimation method for sparse GPS positioning information

Sae Iwata, Tomoyuki Nitta, Toshinori Takayama, Masao Yanagisawa, Nozomu Togawa

    研究成果: Conference contribution

    1 引用 (Scopus)

    抄録

    Cell phones with GPS function as well as GPS loggers are widely used and we can easily obtain users' geographic information. However, still battery consumption in these mobile devices is main concern and then we are not allowed to obtain GPS positioning data so frequently. In this paper, we propose a stayed location estimation method for sparse GPS positioning data. After generating initial clusters from a sequence of measured positions, we set the effective radius for every cluster based on positioning accuracy and merge the clusters effectively using it. After that, we temporarily remove short-time clusters but do not remove measured positions included in them. Then we merge the clusters again, taking all the measured positions into consideration. We perform this process twice, i.e, we perform two-stage short-time cluster removal, and finally realize accurate stayed location estimation even when the GPS positioning interval is five minutes or more. Experiments demonstrate that the total distance error between the estimated stayed location and the true stayed location is reduced by more than 50% compared to a conventional state-of-the-art method.

    元の言語English
    ホスト出版物のタイトル2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
    出版者Institute of Electrical and Electronics Engineers Inc.
    ページ1-5
    ページ数5
    2017-January
    ISBN(電子版)9781509040452
    DOI
    出版物ステータスPublished - 2017 12 19
    イベント6th IEEE Global Conference on Consumer Electronics, GCCE 2017 - Nagoya, Japan
    継続期間: 2017 10 242017 10 27

    Other

    Other6th IEEE Global Conference on Consumer Electronics, GCCE 2017
    Japan
    Nagoya
    期間17/10/2417/10/27

    Fingerprint

    positioning
    Global positioning system
    Mobile devices
    electric batteries
    intervals
    radii
    Experiments
    cells

    ASJC Scopus subject areas

    • Media Technology
    • Instrumentation
    • Electrical and Electronic Engineering

    これを引用

    Iwata, S., Nitta, T., Takayama, T., Yanagisawa, M., & Togawa, N. (2017). A stayed location estimation method for sparse GPS positioning information. : 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017 (巻 2017-January, pp. 1-5). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GCCE.2017.8229230

    A stayed location estimation method for sparse GPS positioning information. / Iwata, Sae; Nitta, Tomoyuki; Takayama, Toshinori; Yanagisawa, Masao; Togawa, Nozomu.

    2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017. 巻 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-5.

    研究成果: Conference contribution

    Iwata, S, Nitta, T, Takayama, T, Yanagisawa, M & Togawa, N 2017, A stayed location estimation method for sparse GPS positioning information. : 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017. 巻. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 6th IEEE Global Conference on Consumer Electronics, GCCE 2017, Nagoya, Japan, 17/10/24. https://doi.org/10.1109/GCCE.2017.8229230
    Iwata S, Nitta T, Takayama T, Yanagisawa M, Togawa N. A stayed location estimation method for sparse GPS positioning information. : 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017. 巻 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-5 https://doi.org/10.1109/GCCE.2017.8229230
    Iwata, Sae ; Nitta, Tomoyuki ; Takayama, Toshinori ; Yanagisawa, Masao ; Togawa, Nozomu. / A stayed location estimation method for sparse GPS positioning information. 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017. 巻 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-5
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    abstract = "Cell phones with GPS function as well as GPS loggers are widely used and we can easily obtain users' geographic information. However, still battery consumption in these mobile devices is main concern and then we are not allowed to obtain GPS positioning data so frequently. In this paper, we propose a stayed location estimation method for sparse GPS positioning data. After generating initial clusters from a sequence of measured positions, we set the effective radius for every cluster based on positioning accuracy and merge the clusters effectively using it. After that, we temporarily remove short-time clusters but do not remove measured positions included in them. Then we merge the clusters again, taking all the measured positions into consideration. We perform this process twice, i.e, we perform two-stage short-time cluster removal, and finally realize accurate stayed location estimation even when the GPS positioning interval is five minutes or more. Experiments demonstrate that the total distance error between the estimated stayed location and the true stayed location is reduced by more than 50{\%} compared to a conventional state-of-the-art method.",
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    AU - Togawa, Nozomu

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    AB - Cell phones with GPS function as well as GPS loggers are widely used and we can easily obtain users' geographic information. However, still battery consumption in these mobile devices is main concern and then we are not allowed to obtain GPS positioning data so frequently. In this paper, we propose a stayed location estimation method for sparse GPS positioning data. After generating initial clusters from a sequence of measured positions, we set the effective radius for every cluster based on positioning accuracy and merge the clusters effectively using it. After that, we temporarily remove short-time clusters but do not remove measured positions included in them. Then we merge the clusters again, taking all the measured positions into consideration. We perform this process twice, i.e, we perform two-stage short-time cluster removal, and finally realize accurate stayed location estimation even when the GPS positioning interval is five minutes or more. Experiments demonstrate that the total distance error between the estimated stayed location and the true stayed location is reduced by more than 50% compared to a conventional state-of-the-art method.

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