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Performance Evaluation of an AmI Testbed for Improving QoL: Evaluation Using Clustering Approach Considering Parallel Processing

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Book cover Advances on Broad-Band Wireless Computing, Communication and Applications (BWCCA 2016)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 2))

Abstract

Ambient intelligence (AmI) deals with a new world of ubiquitous computing devices, where physical environments interact intelligently and unobtrusively with people. AmI environments can be diverse, such as homes, offices, meeting rooms, schools, hospitals, control centers, vehicles, tourist attractions, stores, sports facilities, and music devices. In this paper, we present the design and implementation of a testbed for AmI using Raspberry Pi mounted on Raspbian OS. We analyze the performance of k-means clustering algorithm considering sensing data. For evaluation we considered respiratory rate and heart rate metrics. We speeded up the k-means clustering algorithm by using parallel processing.

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Author information

Authors and Affiliations

  1. Graduate School of Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka, 811–0295, Japan

    Ryoichiro Obukata & Donald Elmazi

  2. Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka, 811–0295, Japan

    Tetsuya Oda, Makoto Ikeda & Leonard Barolli

Authors
  1. Ryoichiro Obukata
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  2. Tetsuya Oda
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  3. Donald Elmazi
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  4. Makoto Ikeda
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  5. Leonard Barolli
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Corresponding author

Correspondence to Tetsuya Oda .

Editor information

Editors and Affiliations

  1. Fukuoka Institute of Technology , Fukuoka, Japan

    Leonard Barolli

  2. Campus Nord,Ed. Omega (Room 109), Technical University of Catalonia Campus Nord,Ed. Omega (Room 109), Barcelona, Spain

    Fatos Xhafa

  3. Department of Information Security Engin, Soonchunhyang University Department of Information Security Engin, Asan-si, Korea (Republic of)

    Kangbin Yim

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Obukata, R., Oda, T., Elmazi, D., Ikeda, M., Barolli, L. (2017). Performance Evaluation of an AmI Testbed for Improving QoL: Evaluation Using Clustering Approach Considering Parallel Processing. In: Barolli, L., Xhafa, F., Yim, K. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2016. Lecture Notes on Data Engineering and Communications Technologies, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-49106-6_61

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  • DOI: https://doi.org/10.1007/978-3-319-49106-6_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49105-9

  • Online ISBN: 978-3-319-49106-6

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