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

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

Qi Zhang
Copyright: © 2024 |Pages: 21
DOI: 10.4018/IJSIR.349216
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Abstract

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.
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Introduction

PE teaching in colleges covers a wide range of areas and needs to meet students' different interests when conducting PE teaching in colleges (Chen, 2019). Some students have a wide range of knowledge. Therefore, it is necessary to meet the actual needs of PE teaching in colleges through more comprehensive hardware facilities. Only a comprehensive application of a teaching platform can provide high-quality PE teaching resources to meet students' needs in different learning forms (Liu, 2020; Li et al., 2022). For example, in colleges, swimming, track and field, football, and basketball are the focus of PE teaching. Physical activity can be combined with professional training through information and communication technology (ICT) to improve the current teaching mode (Pérez & González-Rivera, 2015). PE teaching platform in colleges can fully integrate the actual situation of each student and teaching resources to meet the learning needs of students. Simultaneously, different teaching forms should also be integrated to enhance students' interest in different projects to meet the requirements of PE teaching in colleges, which is increasingly diversified.

In traditional PE teaching in colleges, many sports are more complicated, and it is challenging to master the critical content. To improve the learning effect of students, it is necessary to master the characteristics of sports in a large number of sports through a consistent and scientific-technical way to enhance professional teaching and training. Currently, much of PE teaching in colleges are challenging with time limits, leading to a significant loss of students' learning effect (WenWang & Fan, 2021). To let students truly master a playing skill, enhancing the continuity of action through various teaching means is necessary. Therefore, applying the PE teaching platform in colleges can better monitor students' learning situations.

The traditional PE teaching platform in colleges is usually based on the web, teaching resources, and databases. It is generally presented in the form of teaching videos and HTML. PE teaching in colleges is characterized by practicality and dynamics. By applying the Internet of Things (IoT) and combining the basic situation of PE teaching in colleges, a new teaching platform is built to assist in better teaching and facilitate data collection, storage, and monitoring of PE teaching in colleges. It can grasp the dynamic data of PE teaching in detail and comprehensively and take improvement measures to the existing shortcomings, which is conducive to improving the quality of PE teaching in colleges.

The primary function of IoT is to support the dynamic collection of platform data and to collect various data on PE teaching in colleges by using terminal sensors. The PE teaching platform in colleges should be equipped with sensors to collect data generated during the teaching process. Through the application of IoT and cellular networks, it is conducive to collecting detailed and comprehensive data generated by PE teaching in colleges, analyzing the deficiencies in teaching, and learning according to the teaching and student learning situation, and then developing a personalized teaching guidance plan. This can ensure the accuracy, pertinency, and scientificity of PE teaching in colleges' plans and guidance and promote the smooth progress of PE teaching in colleges, strengthen students' exercise, and improve the teaching effect. For example, in basketball teaching, deficiencies in basketball training can be found by judging students' dribbling trajectory and analyzing dribbling and shooting habits, which is conducive to teachers' better guidance of students' learning and improving basketball skills and techniques. Therefore, the trajectory detection of students is essential.

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