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Sports Analysis and Action Optimization in Physical Education Teaching Practice Based on Internet of Things Sensor Perception.

Authors :
Chen, Mengjunguang
Jiang, Jingjing
Source :
Computational Intelligence & Neuroscience. 6/30/2022, p1-8. 8p.
Publication Year :
2022

Abstract

With the progress of the Internet of things technology in recent years, all aspects of people's lives have also been affected. More and more people are immersed in the virtual world and ignore the real activities. According to the survey, nearly 50% of people in China are in subhealth, mainly modern diseases caused by long-term inactivity. Therefore, to form a good habit of physical exercise, we must start from an early age. Starting from the physical education teaching in primary and secondary schools and from the perspective of modern scientific and technological facilities, this paper discusses the practical sports analysis and action optimization of physical education teaching based on the perception of the Internet of things. Starting from the practice of Internet of things sensor sensing in physical education teaching, we have successively determined the multisensor motion acquisition system algorithm, motion pattern recognition algorithm, and motion energy consumption algorithm, which provides modern equipment for motion analysis and motion optimization in physical education teaching practice, which breaks the current situation that traditional teachers spend a lot of time and energy for students. Combining sports mode with sports energy consumption can not only analyze sports data accurately and in real time but also optimize and predict students' sports behavior in time. We hope to supervise and urge primary and secondary school students to exercise through technical means to improve the quality of primary and secondary school students' exercise and improve people's health through physical exercise. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
157741698
Full Text :
https://doi.org/10.1155/2022/7152953