<p>This study presents an Internet of Things (IoT)-based Physical Education (IoT-PE) framework that integrates wearable sensors, cloud computing, and mobile analytics for real-time monitoring and feedback of health activities. Unlike conventional evaluation methods, IoT-PE autonomously captures physiological and motion data, including heart rate, movement dynamics, and energy expenditure, to deliver instant, data-driven insights. The framework enhances accuracy in performance assessment, ensures consistent feedback, and supports personalized training adaptation through intelligent data visualization. Experimental evaluation demonstrates that IoT-PE enhances the precision of activity monitoring, fosters student engagement, and facilitates more informed decision-making by educators. The proposed system establishes a scalable, interactive, and adaptive model for performance enhancement in physical education.</p>

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Wearable sensors in health activity analysis: real-time monitoring and feedback

  • J. Manikandan,
  • Sheeba Santhosh,
  • V. Mangaiyarkarasi,
  • M. Indirani,
  • D. Revathi,
  • I. Gugan

摘要

This study presents an Internet of Things (IoT)-based Physical Education (IoT-PE) framework that integrates wearable sensors, cloud computing, and mobile analytics for real-time monitoring and feedback of health activities. Unlike conventional evaluation methods, IoT-PE autonomously captures physiological and motion data, including heart rate, movement dynamics, and energy expenditure, to deliver instant, data-driven insights. The framework enhances accuracy in performance assessment, ensures consistent feedback, and supports personalized training adaptation through intelligent data visualization. Experimental evaluation demonstrates that IoT-PE enhances the precision of activity monitoring, fosters student engagement, and facilitates more informed decision-making by educators. The proposed system establishes a scalable, interactive, and adaptive model for performance enhancement in physical education.