Developing an Intelligent Monitoring System for Physical Education Classes in the Context of 5G and Big Data
- DOI
- 10.2991/978-2-494069-05-3_178How to use a DOI?
- Keywords
- 5G; big data; intelligence; IoT; informatization
- Abstract
The development of 5G, Internet of Things (IoT), and intelligent information technology provides strong technical support for monitoring physical education classes. The decline in the physical health of China’s youth has caused widespread concern in society. The State Council of China thus initiated the Sunshine Sports Program and encouraged the youth to exercise one hour a day. Physical education, as an important part of school education, plays a decisive role in enhancing physical fitness among students. Hence, we propose to develop a real-time monitoring system for physical education classes. The system could collect and analyze the data from the classes using Markov models, which enables educational authorities to have easy access to the information related to physical education classes. In addition, for those classes with bad performance, the system will automatically send feedback to relevant educational authorities to keep information updated.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Zhou Dong PY - 2022 DA - 2022/11/19 TI - Developing an Intelligent Monitoring System for Physical Education Classes in the Context of 5G and Big Data BT - Proceedings of the 2022 International Conference on Science Education and Art Appreciation (SEAA 2022) PB - Atlantis Press SP - 1483 EP - 1489 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-05-3_178 DO - 10.2991/978-2-494069-05-3_178 ID - Dong2022 ER -