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International Conference on Broadband and Wireless Computing, Communication and Applications

BWCCA 2019: Advances on Broad-Band Wireless Computing, Communication and Applications pp 698–707Cite as

Mobile Physiological Sensor Cloud System for Long-Term Care

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

Abstract

In this study, we propose a Mobile Physiological Sensor Cloud System for Long-term Care (MPCLC), the main functions of which are collecting carereceiver’s physiological data by using sensors and analyzing and reporting the carereceiver’s healthy condition. With the features of small in size, high convenience for use, and good immediacy of request response, the MPCLC can partially solve the problems of long-term care which are insufficiency of required labors and hard for tracking the results of traditional medical treatment. After the data measured by using sensors is collected, the data is sent to the cloud for storage. The health reports will be generated by the cloud, and delivered to caregivers and medical staffs for reference under their requests. This can save the time that people go and come between hospitals and the places where carereceivers stay for measuring patients’ psysilogical data. One of the other key functions is to prevent the carereceivers from disease in advance.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Tunghai University, Taichung City, 40704, Taiwan

    Ping-Jui Chiang, Fang-Yie Leu & Hui-Ling Huang

  2. Research Center for Informatics, The Indonesian Institute of Sciences, Jakarta, Indonesia

    Heru Susanto

  3. Information Management Department, Tunghai University, Taichung City, 40704, Taiwan

    Heru Susanto

Authors
  1. Ping-Jui Chiang
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  2. Heru Susanto
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  3. Fang-Yie Leu
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  4. Hui-Ling Huang
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Corresponding author

Correspondence to Ping-Jui Chiang .

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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Cite this paper

Chiang, PJ., Susanto, H., Leu, FY., Huang, HL. (2020). Mobile Physiological Sensor Cloud System for Long-Term Care. 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_64

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  • DOI: https://doi.org/10.1007/978-3-030-33506-9_64

  • Published:

  • 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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