Evaluation method of athletes’ special physical fitness based on internet of things

Abstract

Special physical fitness plays an important role in sports skills, improving athletic performance and preventing injuries. Based on the Internet of Things (IoT), the method of assessing athletes’ specific physical fitness is studied using the linear acceleration energy estimation model. After relevant research on the athletes’ real training environment, a real-time monitoring platform is designed. Besides, the MQVA algorithm is proposed, and the simulation experiment is designed. Finally, the accuracy of several algorithms is verified by the practical method of evaluating the application. The verification results show that the precision of the algorithm and the model achieve the expected results. An evaluation model is proposed for individual athletes of the training effect based on the energy consumption rate; for multi-athletes, the indicators used are the progress of energy transfer. This model is compared and verified employing examples. The results show that the evaluation model is accurate and reliable. This investigation is part of the contents of the investigation of the physical fitness training system of the potential advantage project in China. It can provide a theoretical basis for coaches to adopt effective special physical training approaches and methods.