Human activity recognition from environmental background sounds for Wireless Sensor Networks

Yi Zhan, Shun Miura, Jun Nishimura, Tadahiro Kuroda

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    9 Citations (Scopus)

    Abstract

    Sound feature extraction Mel Frequency Cepstral Coefficients (MFCC) and classification Dynamic Time Warping (DTW) algorithms are applied to recognizing the background sounds in the human daily activities. Applying these algorithms to fourteen typical daily activity sounds, average recognition accuracy of 92.5% can be achieved. In these algorithms, how two parameters (Le., Mel filters number and frame-to-frame overlap) affect system's calculation burden and accuracy is also investigated, By adjusting these two parameters to a suitable combination, the calculation burden can be reduced by 61.6% while maintaining the system's average accuracy rate at approximate 90%. This is promising for future integrating with other sensor(s) to fulfill daily activity recognition work by using power aware Wireless Sensor Networks (WSN) system.

    Original languageEnglish
    Title of host publication2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
    Pages307-312
    Number of pages6
    DOIs
    Publication statusPublished - 2007 Oct 1
    Event2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07 - London, United Kingdom
    Duration: 2007 Apr 152007 Apr 17

    Publication series

    Name2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07

    Other

    Other2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
    CountryUnited Kingdom
    CityLondon
    Period07/4/1507/4/17

    Keywords

    • Calculation burden
    • DTW
    • MFCC
    • Sound recognition
    • WSN

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Control and Systems Engineering

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  • Cite this

    Zhan, Y., Miura, S., Nishimura, J., & Kuroda, T. (2007). Human activity recognition from environmental background sounds for Wireless Sensor Networks. In 2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07 (pp. 307-312). [4239009] (2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07). https://doi.org/10.1109/ICNSC.2007.372796