Welcome to Francis Academic Press

Frontiers in Sport Research, 2024, 6(5); doi: 10.25236/FSR.2024.060508.

Research on the Path of Artificial Intelligence Enabling Free Diving Training

Author(s)

Zhang Zhenyu

Corresponding Author:
Zhang Zhenyu
Affiliation(s)

School of Sports Science, Lingnan Normal University, Zhanjiang City, 524048, China

Abstract

With the integration of artificial intelligence (AI) technology, its value in the field of sports training has become increasingly prominent. Specifically in the extreme sport of free diving, the involvement of AI has opened up new horizons for the innovation and upgrading of training methods. This article explores the potential of AI in free diving training and constructs a framework for AI-based free diving training. The framework is grounded in the theory of digital intelligence empowerment, leveraging data collection, processing, and in-depth analysis to accurately grasp the athlete's status and provide personalized guidance and real-time feedback. Additionally, the integration of virtual reality technology creates an immersive training environment, enhancing the authenticity and sense of participation. AI enables free diving training to reach new heights, improving efficiency and safety. In the future, AI will continue to play a role in the field of sports training, bringing more possibilities to athletes. This research first explores the inherent logic of AI-enabled free diving training, clarifying the core elements such as data-driven, personalized guidance, intelligent monitoring, and interactive experiences. Secondly, by referring to international successful cases and experiences, this study proposes a localized practical framework, encompassing the construction of technical systems, organizational systems, and environmental spaces. The technical system is responsible for data collection, processing, and analysis, providing scientific and precise training guidance for athletes. The organizational system ensures the smooth implementation and effective management of the project. Meanwhile, the environmental space provides necessary physical and virtual training spaces for athletes. Through empirical research, this article validates the effectiveness and practicality of the framework, providing new ideas and methods for the innovation and development of free diving training. This research not only enriches the application research of AI in the field of sports training, but also provides strong support for the sustainable development of free diving. In the future, with the continuous advancement of technology and the expansion of application scenarios, the application of AI in free diving training will become more extensive and in-depth.

Keywords

Artificial Intelligence; Free Diving Training; Digital Intelligence Empowerment

Cite This Paper

Zhang Zhenyu. Research on the Path of Artificial Intelligence Enabling Free Diving Training. Frontiers in Sport Research (2024) Vol. 6, Issue 5: 48-54. https://doi.org/10.25236/FSR.2024.060508.

References

[1] Benbya, H., Pachidi, S., & Jarvenpaa, S.. Special issue editorial: Artificial intelligence in organizations: Implications for information systems research[J]. Journal of the Association for Information Systems, 2021, 22(2), 281–303.

[2] Claudino JG, et al. Current approaches to the use of artificial intelligence for injury risk assessment and performance prediction in team sports: a systematic review. Sports Med Open. 2019;5:1–12.

[3] Kos A, Umek A. Wearable sensor devices for prevention and rehabilitation in healthcare: Swimming exercise with real-time therapist feedback. IEEE Internet Things J, 2018, 6(2):1331–1341.

[4] Fan Wei. Research on Logistics Network Information Security Management Methods Based on Big Data [J]. Network Security Technology and Application, 2024, (07): 78-80.

[5] Kou Xiaona. A Brief Discussion on the Impact and Implications of Artificial Intelligence on the Development of Competitive Sports in China [J]. Contemporary Sports Technology, 2018, 8(28): 203-204. DOI: 10.16655/j.cnki.2095-2813.2018.28.203.

[6] Yue Xiaodong. Establishment Method of Autonomous Learning Model for System Fault Prediction [J]. Electronic Technology and Software Engineering, 2017, (12): 172.

[7] Zhang Yue. Analysis of the Development Trend and Strategies of Combining Sports Information Technology with Sports Training [J]. Sports Goods and Technology, 2024, (13): 127-129.

[8] Hao Zhili. Research on High-quality Development of Sports Industry Empowered by Artificial Intelligence (AI) [J]. Sports Goods and Technology, 2024, (13): 181-183. 

[9] Xiong Yan, Jia Wenjie. Scientific Analysis of Sports Training [J]. Journal of Tianjin University of Sport, 2024, 39(03): 326-332+349. DOI: 10.13297/j.cnki.issn1005-0000.2024.03.011.