Cloud IoT-Oriented Secure College Physical Education Teaching Platform Vased on Deep Learning

In physical education (PE) teaching, the teaching platform is comprehensively applied to provide students with high-quality PE teaching resources to meet their learning needs in different forms. A human motion trajectory detection method is proposed based on deep learning and superpixels. The initial positioning of human body is performed through the attention mechanism and the YOLOv5 model, and the human target tracking is performed through superpixels. Aiming at the difficulty of cross-domain security management due to the lack of security infrastructure in multi-domain cloud IoT, a lightweight certificateless cross-domain authentication scheme is designed. Simulation results show that the proposed detection method has significantly improved accuracy and running time compared with traditional methods and can adapt to different detection scenarios. Furthermore, the proposed certificateless cross-domain authentication scheme can securely access sensor-generated data under the cloud IoT of the PE teaching platform in colleges.