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Prediction of RSSI by Scikit-Learn for Improving Position Detecting System of Omnidirectional Wheelchair Tennis

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Advances on Broad-Band Wireless Computing, Communication and Applications (BWCCA 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 97))

Abstract

The wheelchair with good performance for the aged and disabled people is attracting attention from the society. Also, the wheelchair can provide the user with many benefits, such as maintaining mobility, continuing or broadening community social activities, conserving energy and enhancing quality of life. The wheelchair body must be compact enough and should be able to make different movements in order to have many applications. In our previous work, we presented the design and implementation of an omnidirectional wheelchair. In this paper, we propose a position detecting system for improving the performance of omnidirectional wheelchair tennis. This is achieved by predicting RSSI value using Scikit-learn. The proposed system can find correctly the wheelchair position for avoiding the collision.

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Authors and Affiliations

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

    Keita Matsuo & Leonard Barolli

Authors
  1. Keita Matsuo
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  2. Leonard Barolli
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Corresponding author

Correspondence to Keita Matsuo .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electronics, University of Antwerp, Antwerp, Belgium

    Peter Hellinckx

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

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Matsuo, K., Barolli, L. (2020). Prediction of RSSI by Scikit-Learn for Improving Position Detecting System of Omnidirectional Wheelchair Tennis. In: Barolli, L., Hellinckx, P., Enokido, T. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2019. Lecture Notes in Networks and Systems, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-33506-9_66

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  • DOI: https://doi.org/10.1007/978-3-030-33506-9_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33505-2

  • Online ISBN: 978-3-030-33506-9

  • eBook Packages: EngineeringEngineering (R0)

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