Abstract
Using artificial intelligence recognition algorithms to identify extracurricular physical exercise behaviors of college students can help teachers improve the efficiency of extracurricular management, improve student safety and physical exercise efficiency. Aiming at the characteristics of classroom physical exercise mode, this research uses UHF RFID technology to design a set of student information collection system. Moreover, this research processes the collected information and data to obtain the individual position of the student and combines with student action recognition to carry out student positioning and action recognition management. In addition, in order to explore the effect of artificial intelligence sports monitoring model in sports action recognition, this study uses the average recognition rate as a measure of the results of sports action recognition and uses neural network algorithms as a comparative experiment. From the experimental results, it can be seen that the performance of this algorithm is good, and it can be applied to the supervision of college students’ extracurricular physical exercise.
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