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IoT inspired smart environment for personal healthcare in gym

  • S.I. : Neural Computing for IOT based Intelligent Healthcare Systems
  • Published:
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Abstract

The Internet of Things (IoT) has the ability to collect health-related data from surroundings. As a result, the Cloud Centric IoT (CCIoT) Technology is used in this paper to measure a trainee’s health-related traits during fitness time in a gym. The proposed system can forecast a trainee’s probabilistic sensitivity to health status during workouts. Back-propagation based Artificial Neural Network (ANN) methodology is used as a prediction model for this purpose, and it is divided into 3 phases: Observation, Learning, and Prediction. In addition, the trainee’s health status is depicted in real-time using a colour scheme strategy that depicts the probabilistic vulnerability. The presented framework was tested by a 6 day trial in which five individuals were supervised at various gymnasiums. For assessing the general efficacy of the proposed framework, the outcomes are compared to various state-of-the-art approaches in terms of prediction efficiency, temporal prediction, and stability.

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  1. College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia

    Tariq Ahamed Ahanger

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  1. Tariq Ahamed Ahanger
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Correspondence to Tariq Ahamed Ahanger.

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Ahanger, T.A. IoT inspired smart environment for personal healthcare in gym. Neural Comput & Applic 35, 23007–23023 (2023). https://doi.org/10.1007/s00521-022-07488-8

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  • DOI: https://doi.org/10.1007/s00521-022-07488-8

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