Research Article
Design of Aerobics Network Teaching System Based on Artificial Intelligence
@INPROCEEDINGS{10.1007/978-3-031-21161-4_4, author={Rong Sun and Zhaoqi Fu}, title={Design of Aerobics Network Teaching System Based on Artificial Intelligence}, proceedings={e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9--10, 2022, Proceedings, Part I}, proceedings_a={ELEOT}, year={2023}, month={3}, keywords={Artificial intelligence Aerobics Network teaching Teaching system Meanshif algorithm}, doi={10.1007/978-3-031-21161-4_4} }- Rong Sun
Zhaoqi Fu
Year: 2023
Design of Aerobics Network Teaching System Based on Artificial Intelligence
ELEOT
Springer
DOI: 10.1007/978-3-031-21161-4_4
Abstract
The traditional network teaching system uses network video for aerobics teaching, which can not effectively correct students’ movements. At the same time, its recommended resources are difficult to match students’ learning ability, and can not provide targeted intensive training resources. In order to realize remote intelligent aerobics teaching and improve the teaching effect of aerobics course, an aerobics network teaching system based on artificial intelligence is designed. In the process of hardware design, the control module and peripheral function module are optimized. The software part uses the meanshif algorithm to track the students’ bone information collected by Kinect, so as to correct the aerobics movement. At the same time, the neural network is used to improve the recommendation algorithm. According to the students’ learning and action correction, aerobics teaching resources are recommended to meet the needs of students at different stages. The system performance test results show that after the application of the designed system, the action standard rate of students is increased to more than 90%, and the accuracy rate of Resource Recommendation is higher than 90%.
