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Symbiotic Construction of Individual's Rich Location Dataset

Published: 08 October 2018 Publication History

Abstract

Sensing our daily activities is essential for ubiquitous computing. Although smartphones and wearable devices can easily collect their owner's data, continuous sensing causes battery drain and consumes CPU power of those devices. This paper proposes a brand new framework utilizing the symbiotic construction of an individual's location dataset, one of the most typical daily activities, by combining infrequent sensed location logs of serendipitously nearby users including strangers. The proposed method estimates the location where the user was using other users' sensed sparse location logs. The user can obtain his/her detailed dense location history without increasing sensing frequency and CPU load of his/her device compared to those for normal daily use. Experimental results show a rich location dataset of the user can be estimated.

References

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I. Agadakos, J. Polakis, G. Portokalidis. 2017. Techu: Open and Privacy-Preserving Crowdsourced GPS for the Masses. In Proc. MobiSys 2017. 475--487.
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S. Cho, C. Julien. 2016. CHITCHAT: Navigating Tradeoffs in Device-to-Device Context Sharing. In Proc. PerCom 2016. 1--10.
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O. Helgason, S. T. Kouyoumdjieva, G. Karlsson. 2014. Opportunistic Communication and Human Mobility. IEEE Trans. Mobile Comput. 13, 7 (2014), 1597--1610.
[4]
H. Kurasawa et al. 2014. Missing Sensor Value Estimation Method for Participatory Sensing Environment. In Proc. 2014 PerCom. 103--111.
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Y. Lee et al. 2012. CoMon: Cooperative Ambience Monitoring Platform with Continuity and Benefit Awareness. In Proc. MobiSys 2012. 43--56.

Cited By

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  • (2020)Parasitic Location Logging: Estimating Users’ Location from Context of Passersby2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PerCom45495.2020.9127381(1-10)Online publication date: Mar-2020

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  1. Symbiotic Construction of Individual's Rich Location Dataset

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    cover image ACM Conferences
    UbiComp '18: Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
    October 2018
    1881 pages
    ISBN:9781450359665
    DOI:10.1145/3267305
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 08 October 2018

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    Author Tags

    1. Data Sharing
    2. Location Logging

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    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    • (2020)Parasitic Location Logging: Estimating Users’ Location from Context of Passersby2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)10.1109/PerCom45495.2020.9127381(1-10)Online publication date: Mar-2020

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