Research on the application technology of Artificial Intelligence in college physical education and training

Nowadays, with the swift advancement of Artificial Intelligence (AI) technology, its applications have become widespread across diverse fields. AI is no longer a mere abstract idea but has seamlessly integrated into our daily lives, bringing numerous conveniences through its myriad benefits. One such domain where AI has made significant inroads in college physical education and training. The integration of Intelligent Computer-Aided Instruction (ICAI) with computer-assisted teaching systems, AI-powered wearable devices, motion capture systems in sports training, and virtual demonstration technology for simulating athletic movements has greatly enhanced both the precision of physical education and the efficacy of physical training. AI continues to evolve rapidly, indicating vast potential for further development in its integration with physical education and training. This paper highlights the widespread adoption of AI in sports and delves into its specific applications within this domain. The findings reveal that the algorithm employed in this context excels in identifying sports movement features, outperforming the comparison algorithm by 27.65%. Moreover, it precisely pinpoints the edge contours of human movement. In comparison to traditional Support Vector Machines (SVM), Convolutional Neural Networks (CNN) exhibit clear advantages during the later stages of operation, reducing errors by 36.69%. The experimental results underscore the importance of comprehensive human body detection in ensuring stable and accurate sports action tracking. © 2024 Min Mao and Jianxing Chen, published by Sciendo.