The improvements in health habits, technological advances, and the proliferation of healthy living activities have contributed to the comprehensive extension of sports person health assessment. Since the internet of things (IoT) device requires energy‐optimized wearable devices, it has been observed that the demanding factors include energy efficiency factor in Sports Person Health Monitoring wearable device. Hence in this paper, IoT‐based Hierarchical Health Monitoring Model (IoT‐HHMM) is proposed to improve the efficiency factor by minimizing the energy consumption to achieve effective assessment of sports person health monitoring wearables. The complexity of limited resources and usage of energy is optimized by introducing the Optimal Energy‐Efficient Resource Assignment Algorithm. Likewise, a cloud computing technique is implemented using Probabilistic Radial Basis Function Neural Network to ensure effective prediction and classification in healthcare data management, which is considered as a significant factor in wearable IoT devices for Sports Person Health Monitoring. The result indicates that the proposed IoT‐HHMM achieves a high accuracy ratio of 98.4%, a sensitivity ratio of 92.5%, a performance ratio of 96.7% when compared to traditional approaches.

Introduction: We should pay attention to physical and psychological training still in the growth phase of athletes to ensure a better overall performance quality. Psychological training can be an effective tool to improve the technical level and skills of swimming. Objective: This paper discusses the relationship between mental health education and training intensity in college swimmers. Methods: The mental health of professional swimmers in college sports is explored with study subjects undergoing a 10-week training trial. The comparison of clinical effects between various psychological training modalities and swimmers’ self-management is analyzed. In a second step, this paper performs statistics and analysis on the questionnaire and experimental data. Results: The exercise ability of the control group was significantly improved after relaxation training, tension training, and thought control training (P<0.05). The results showed that the learning effect of the experimental group was significantly better than that of the control group (P<0.05). Conclusion: Psychological training and self-regulation in training have a good effect on improving the mental quality of competitive sports players. This approach improves athletes’ performance more effectively than other approaches. The psychological self-regulation training method is one that swimming coaches should pay attention to and advocate vigorously. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

With the development of sports in colleges and universities, the research on innovation reform of sports industry has been deepened. Therefore, based on the above situation, a study of the status quo and development direction of sports industry in colleges and universities based on the Euclid algorithm is proposed. In the research here, according to the traditional sports industry concept to sum up, and then according to the advantages of computer technology to deal with the relevant data. In order to realize good overlap between data, an application of Euclidean algorithm is proposed. In the test of Euclidean algorithm, the efficiency and function of the algorithm are tested comprehensively, and the test results show that the research is feasible.