Online Change Detection for Energy-Efficient Mobile Crowdsensing

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)
    25 Downloads (Pure)

    Abstract

    Mobile crowdsensing is power hungry since it requires continuously and simultaneously sensing, processing and uploading fused data from various sensor types including motion sensors and environment sensors. Realizing that being able to pinpoint change points of contexts enables energy-efficient mobile crowdsensing, we modify histogram-based techniques to efficiently detect changes, which has less computational complexity and performs better than the conventional techniques. To evaluate our proposed technique, we conducted experiments on real audio databases comprising 200 sound tracks. We also compare our change detection with multivariate normal distribution and one-class support vector machine. The results show that our proposed technique is more practical for mobile crowdsensing. For example, we show that it is possible to save 80% resource compared to standard continuous sensing while remaining detection sensitivity above 95%. This work enables energy-efficient mobile crowdsensing applications by adapting to contexts.
    Original languageEnglish
    Title of host publicationMobile Web Information Systems
    Subtitle of host publication11th International Conference on Mobile Web and Information Systems, MobiWIS 2014
    EditorsIrfan Awan, Muhammad Younas, Xavier Franch, Carme Quer
    Place of PublicationLondon
    PublisherSpringer
    Pages1-16
    Number of pages16
    ISBN (Electronic)978-3-319-10359-4
    ISBN (Print)978-3-319-10358-7
    DOIs
    Publication statusPublished - 27 Aug 2014
    Event11th International Conference on Mobile Web and Information Systems, MobiWIS 2014 - Barcelona, Spain
    Duration: 27 Aug 201429 Aug 2014
    Conference number: 11

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Volume8640
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference11th International Conference on Mobile Web and Information Systems, MobiWIS 2014
    Abbreviated titleMobiWIS
    CountrySpain
    CityBarcelona
    Period27/08/1429/08/14

    Keywords

    • CAES-PS: Pervasive Systems
    • EWI-25022
    • Energy Efficiency
    • Resource Constraints
    • METIS-309573
    • Change Detection
    • Adaptive Sensing
    • Computational Complexity
    • Mobile Crowdsensing
    • IR-92420

    Fingerprint Dive into the research topics of 'Online Change Detection for Energy-Efficient Mobile Crowdsensing'. Together they form a unique fingerprint.

  • Cite this

    Le Viet Duc, D. V., Scholten, J., & Havinga, P. J. M. (2014). Online Change Detection for Energy-Efficient Mobile Crowdsensing. In I. Awan, M. Younas, X. Franch, & C. Quer (Eds.), Mobile Web Information Systems: 11th International Conference on Mobile Web and Information Systems, MobiWIS 2014 (pp. 1-16). (Lecture Notes in Computer Science; Vol. 8640). London: Springer. https://doi.org/10.1007/978-3-319-10359-4_1