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Enhanced Sensing and Activity Recognition System Using IoT for Healthcare

Enhanced Sensing and Activity Recognition System Using IoT for Healthcare

Yamini G., Gopinath Ganapathy
Copyright: © 2021 |Volume: 13 |Issue: 2 |Pages: 8
ISSN: 1935-5661|EISSN: 1935-567X|EISBN13: 9781799860051|DOI: 10.4018/IJICTHD.2021040103
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MLA

Yamini G., and Gopinath Ganapathy. "Enhanced Sensing and Activity Recognition System Using IoT for Healthcare." IJICTHD vol.13, no.2 2021: pp.42-49. http://doi.org/10.4018/IJICTHD.2021040103

APA

Yamini G. & Ganapathy, G. (2021). Enhanced Sensing and Activity Recognition System Using IoT for Healthcare. International Journal of Information Communication Technologies and Human Development (IJICTHD), 13(2), 42-49. http://doi.org/10.4018/IJICTHD.2021040103

Chicago

Yamini G., and Gopinath Ganapathy. "Enhanced Sensing and Activity Recognition System Using IoT for Healthcare," International Journal of Information Communication Technologies and Human Development (IJICTHD) 13, no.2: 42-49. http://doi.org/10.4018/IJICTHD.2021040103

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Abstract

Through the integration of advanced algorithms and smart sensing technology in healthcare services, huge medical benefits could be gained by the aged and sick people in determining their activity recognition. Human activity recognition (HAR) is still in the research for the past decades that promotes recognition of physical activities automatically. The main aim of HAR is to obtain and analyze the physical activities of a person, which could be promoted through several in-built sensors examined in the form of video data. Through this technique, necessary information could be obtained that also helps in preventing significant risks and also averts or alerts unfortunate events from happening. However, there is no particular categorization for human activity, and there is no description of the particular events to occur. The objective of this paper is to propose a healthcare information system based on IoT where enhancing activity recognition is the primary focus. Human activities are supposed to be diverse; it is necessary to choose appropriate sensors and the effective placement of those sensors in recognizing specific activities. One of the major challenges here is choosing the appropriate sensor for that particular instance and gathering data under particular circumstances. Due to the large coupling of sensors and their activity monitoring functionality, the solution to promote feasibility for the HAR predicament cannot be determined. A distinguishing feature of this paper is that it includes future users' perspectives.

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