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A SVM Algorithm for Falling Detection in an IoTs-Based System

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A Handbook of Internet of Things in Biomedical and Cyber Physical System

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 165))

Abstract

Falling of elderly people is one of main reasons causing serious injuries or the risk of early death. However, this may be reduced by using an IoTs-based fall detection system, in which a SVM algorithm and PCA features are applied. In addition, datasets collected from tri-axial accelerometer sensors and/or Kinect camera systems are transferred to a central Hub via Zigbee interface and are updated continuously to a cloud server for processing and detecting fall states. In addition, fall messages can be sent to relatives through smartphones and/or healthcare centers for alert and supporting soon. Experimental results show to illustrate the effectiveness of the proposed system.

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Acknowledgements

The authors would like to acknowledge the support the HCMC University of Technology and Education, Vietnam. In addition, we would like to thank you master students for supports in our research.

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Authors and Affiliations

  1. Department of Industrial Electronic-Biomedical Engineering, HCMC University of Technology and Education, HCM City, Vietnam

    Thanh-Hai Nguyen & Ba-Viet Ngo

  2. Department of Biomedical Engineering, International University-Vietnam National University, HCM City, Vietnam

    Thanh-Tam Nguyen

Authors
  1. Thanh-Hai Nguyen
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  2. Thanh-Tam Nguyen
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  3. Ba-Viet Ngo
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Corresponding author

Correspondence to Thanh-Hai Nguyen .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  2. Department of CSE, CMR Institute of Technology (Autonomous), Hyderabad, Telangana, India

    Vijender Kumar Solanki

  3. Department of Computer Science and Engineering, LNCT Group of College, Jabalpur, Madhya Pradesh, India

    Raghvendra Kumar

  4. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Md. Atiqur Rahman Ahad

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Nguyen, TH., Nguyen, TT., Ngo, BV. (2020). A SVM Algorithm for Falling Detection in an IoTs-Based System. In: Balas, V., Solanki, V., Kumar, R., Ahad, M. (eds) A Handbook of Internet of Things in Biomedical and Cyber Physical System. Intelligent Systems Reference Library, vol 165. Springer, Cham. https://doi.org/10.1007/978-3-030-23983-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-23983-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23982-4

  • Online ISBN: 978-3-030-23983-1

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