IoT-assisted physical education training network virtualization and resource management using a deep reinforcement learning system

Abstract

The Internet of Things (IoT) development made it possible for technology to communicate physical education by connecting cost-effective heterogeneous devices and digital applications to uncontrolled and accessible environments. The traditional physical education monitoring environment creates crucial manual efforts on athletes' activity observations and tracking consistently. Similarly, remote monitoring and assessment of athletes in sports training seem to be barriers to physical education monitoring and training. It creates various chances to improve training and education through technology advancements like IoT and deep learning. Students can efficiently monitor their physical behavior to increase their physical and psychological benefits. The IoT-assisted physical activity monitoring device is proposed to track students' physical activity and enhance outcomes. The management ability allows students to organize and increase speed their physical activity in a wellness manner. In addition, this study examines the connections between monitoring ability which is an essential component for sports activities and physical activity. This system collects essential information from IoT-based wearable devices that interact with the data in real time by virtualizing the device. The IoT network includes several device activities and monitors the heartbeat and physical body temperature of a person. The analysis of specific studies and student feedback shows that the designed virtual system of physical educations is effective in its application and implementation and provides a reliable guide for developing student physical educational systems. The experimental analysis is evaluated; the solution offered is developing and supporting physical education and training approaches in reality and creates healthy environment systems to solve the health monitoring challenges posed by IoT devices. The proposed method has achieved extraordinary physical activity monitoring compared to the conventional systems, as shown by experimental findings. The simulation analysis of physical education can help students and improve the associated aspects of physical abilities with high accuracy ratio (98.3), prediction ratio (96.5%), interaction ratio (94.4%), performance ratio (95.1%), the efficiency ratio (93.2), F-score (92.2%), and reduce error rate (17.5%) and physical activity patterns.

Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication

“…The future of somatic cultivation shall be highly personalized, humanized, and creative under the guidance of AI methodology that has an incalculable effect on physical education and improves the fast emergence of physical education, as shall be seen with the perpetual perfection of scientific and technological standards and the perpetual advancement of the time [ 39 ]. In addition to this, the researcher found that IoT-PAMD strategy helps to identify the student's physical health for additional monitoring [ 40 ].…”

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

“…The wide application of machine vision technology in industrial automation has promoted the research process of the entire discipline and has gradually developed into a multidisciplinary science and technology such as image processing technology, computer vision technology, pattern recognition technology, artificial intelligence, and artificial nerves. A deep learning method is added on the basis of machine vision, which not only improves the efficiency of workpiece detection but also solves the detection problem of small batches and various types of workpieces in industrial production, thereby accelerating the process of intelligent workpiece detection [10]. Pattern recognition technology can be accomplished through deep learning algorithms.…”

Laboratory Virtualization Management Based on Deep Integration of Cloud Desktop

“…With the continuous improvement of the level of social informatization, as well as the popularization of computer applications, computers have become an indispensable common tool in all walks of life; the ability to operate and use computers has also become one of the necessary skills for contemporary college students. All majors in colleges and universities, whether it is science or literature and history, require students to have the ability to use computers to process and solve problems [1]. To this end, colleges and universities around the world invest a lot of money every year to build, rebuild, and expand computer laboratories, creating good hardware conditions for the cultivation of students' computer practice ability.…”