Research On Intelligent Technologies Of 100m Campus Sports Training For The Integration Of Sports And Education

At present,the sustainable development of campus sports training in China faces many problems and cannot meet the needs of talent training under the policy of integration of sports and education.In view of this,this study drew on the advanced experience of 100 m sports training in China’s competitive sports and introduces cutting-edge technologies in the field of artificial intelligence to conduct research on the intelligent technologies for the whole process of campus 100 m sports training including monitoring,analysis and decision-making.First,in the intelligent monitoring phase,the design and validation of an intelligent monitoring scheme for campus 100 m sports training was completed with artificial intelligence and sensor technologies.Then,in the intelligent analysis phase,we optimized the mathematical model of speed rhythm of 100 m,designed a biomechanical parameter extraction algorithm for campus 100 m sports training,and compared the speed rhythm features and biomechanical parameters of student athletes with the technical indexes of elite athletes.Finally,in the intelligent decision-making phase,a causal decision making algorithm based on "champion model" was proposed to simulate the decision making process of elite human coaches and give training suggestions.The main conclusions and contributions of the research are as follows.(1)This paper proposes a convenient and efficient campus 100 m monitoring scheme based on human pose estimation algorithm,which uses a high-speed camera to collect data,uses the Media Pipe algorithm to process data,with optimization combining the spatio-temporal motion characteristics of the 100 m event.The validation experimental results show that the scheme can obtain the accuracy close to the 3D motion capture algorithm of multiple cameras and reduce the human and material costs at the same time to meet the realistic needs of campus sprint sports training.(2)This paper introduces a 3-parameter mathematical model of 100 m speed rhythm,and an intelligent analysis algorithm for key parameters such as stride length,stride frequency,touchdown time,and takeoff time.The results of the comparative analysis show that the main difference between college 100 m athletes and elite athletes in terms of speed rhythm is poorer speed endurance,and the main difference in terms of sports biomechanical parameters compared with elite athletes is shorter stride length,which provides a quantitative basis for the scientific diagnosis of campus sprint sports technology.(3)This paper introduces causal inference method in sports science research practice,simulating the decision-making experience of elite coaches’ "champion model",which is free from the reliance on predetermined rules or human assistance in decision-making.The case and experimental results show that the method can simulate Randy Huntington’s technical diagnosis of Bingtian Su’s speed rhythm in the Tokyo Olympics,and also provide personalized technical diagnosis for college athletes,and provides a new idea to solve the problem that human coaches’ cognitive decisions cannot be replicated,and to achieve the intelligent closed loop of sports training.