Physical education and its role in improving the health of college students by active participation and optimization by deep learning

Abstract

Lack of physical exercise leads to many complicated diseases such as obesity, diabetes, and cardiovascular diseases, or even death in certain cases. College students are at an age where their physical activity levels decline. Physical education may be beneficial in preserving the student's life and improve their health condition. This paper aims to provide support and optimization using a deep learning approach for the students in their college environment. Deep Learning (DL) allows the students to create their areas of interest and set their own rules, leading to active participation. DL increases the students' level of participation by providing effective communication, collaboration, creativity, technological advancement, critical thinking, personalized and real-time learning. The participation of the students can be initiated by allowing them to select a game and exercise routine in their area of interest. If one team does exercise, then another team will participate in the game of their choice. With the help of DL, they can change a rule or adapt a constant. With a lot of training, they will figure out how to excel in their physical activity. This program aims to involve everyone in this task, and nobody should be left out. The critical aspects such as the low performance of a student in physical activity are considered significantly critical and should be maximized to improve the accuracy of the student's performance. Students should take their failure as an opportunity to discover an alternate approach to succeed in it. Optimization is provided by selecting the best approach for each student from the set of available approaches by reducing the student's perception level and increase motivation to engage in each activity. Physical training has a positive impact on the student's health with a 94% increase in energy expenditure and 82% in the fitness rate of the students. The deep learning approach used maximized efficiency in increasing the students' participation and performance level up to 92%.