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A Data Processing Method for Human Motion Estimation to Reduce Network and Sensor Node Loads

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  • Shintaro Imai

    (Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan)

  • Mariko Miyamoto

    (Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan)

  • Mingrui Cai

    (Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan)

  • Yoshikazu Arai

    (Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan)

  • Toshimitsu Inomata

    (Graduate School of Software and Information Science, Iwate Prefectural University, Takizawa, Japan)

Abstract

Systems for estimating human motion using acceleration sensors present the following two problems: 1) advanced analysis and processing of sensor data are difficult because of resource limitations of sensor nodes; and 2) such analyses and processes burden the network because numerous sensor data are sent to the network. The authors’ proposed method described herein for sensor data analysis and processing uses a host computer located near sensor nodes (neighborhood host). This method is intended to achieve a good balance between reduction of the network load and advanced sensor data analysis and processing. Moreover, this method incorporates reduction of the load to sensor nodes. To evaluate their method, the authors implement two prototype systems that use different machine learning methods. The authors conduct some experiments using these prototype systems. The experimentally obtained results demonstrate that the proposed method can resolve two problems.

Suggested Citation

  • Shintaro Imai & Mariko Miyamoto & Mingrui Cai & Yoshikazu Arai & Toshimitsu Inomata, 2013. "A Data Processing Method for Human Motion Estimation to Reduce Network and Sensor Node Loads," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 7(1), pages 58-74, January.
  • Handle: RePEc:igg:jcini0:v:7:y:2013:i:1:p:58-74
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