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SensingGO: Toward Mobile/Cellular Data Measurement with Social and Rewarding Activities

Published: 15 October 2018 Publication History

Abstract

Mobile Crowd Sensing (MCS) is a promising paradigm to collect large-scale network data globally. However, how to motivate people to collect and share data is a challenge. We believe the major reason why many MCS systems are not pervasive is because there are no incentives for people to use them. In this paper, we present SensingGO, a system which encourages people to keep sensing data by integrating incentive mechanisms. The sensed data are then transmitted to our backend server. The data we collected and the source code of SensingGO are open to anyone freely. We also demonstrate the analysis of real mobile data collected from SensingGO.

References

[1]
A. Nikravesh, et al. 2015. Mobilyzer: An open platform for controllable mobile network measurements. In Proc. of MobiSys. 389--404.
[2]
Mikhail Bilenko and Raymond J Mooney. 2003. Adaptive duplicate detection using learnable string similarity measures. In Proc. of SIGKDD. 39--48.
[3]
Aaron Clauset, Cosma Rohilla Shalizi, and Mark EJ Newman. 2009. Power-law distributions in empirical data. SIAM review, Vol. 51, 4 (2009), 661--703.
[4]
Bin Guo, Zhiwen Yu, Xingshe Zhou, and Daqing Zhang. 2014. From participatory sensing to mobile crowd sensing. In Proc. of PERCOM Workshops.
[5]
Yakov Shafranovich. 2005. Common format and MIME type for comma-separated values (CSV) files. (2005).

Cited By

View all
  • (2020)5G trackerProceedings of the SIGCOMM '20 Poster and Demo Sessions10.1145/3405837.3411394(65-67)Online publication date: 10-Aug-2020
  • (2020)Mobility Prediction at Points of Interest Using Many-to-one Recurrent Neural NetworkGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9322343(1-6)Online publication date: Dec-2020

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  1. SensingGO: Toward Mobile/Cellular Data Measurement with Social and Rewarding Activities

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    cover image ACM Conferences
    MobiCom '18: Proceedings of the 24th Annual International Conference on Mobile Computing and Networking
    October 2018
    884 pages
    ISBN:9781450359030
    DOI:10.1145/3241539
    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: 15 October 2018

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    Author Tags

    1. mobile applications and services
    2. mobile crowd sensing

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    • Ministry of Science and Technology

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    MobiCom '18 Paper Acceptance Rate 42 of 187 submissions, 22%;
    Overall Acceptance Rate 440 of 2,972 submissions, 15%

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    Cited By

    View all
    • (2020)5G trackerProceedings of the SIGCOMM '20 Poster and Demo Sessions10.1145/3405837.3411394(65-67)Online publication date: 10-Aug-2020
    • (2020)Mobility Prediction at Points of Interest Using Many-to-one Recurrent Neural NetworkGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9322343(1-6)Online publication date: Dec-2020

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