Strategy for improving the football teaching quality by AI and metaverse-empowered in mobile internet environment

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Abstract

The metaverse has influenced the development of science and technology since it was proposed. While artificial intelligence (AI) is still one of the important technologies to solve problems in metaverse. The success of AI in various fields and the development of information technology make the integration of sports industry and AI an inevitable trend. Currently, the traditional physical education is experiencing qualitative changes, and the demand of integrating AI and metaverse into physical education is becoming more and more obvious. Football teaching is an important part of physical education, and Virtual Reality (VR) has the characteristics of immersion, interaction and imagination, which can build virtual and realistic football teaching process. In this study, through 360-degree panoramic VR football teaching videos empowered by the metaverse and K-means algorithm based on machine learning under AI, we study the strategies for improving the quality of football teaching in the mobile Internet environment. Therefore, we propose K-means based optimized 360-degree panoramic VR football teaching video delivery strategy. In addition, we conduct simulation experiments under content delivery networks simulator, and the simulation results show that the proposed strategy is superior to the baselines in terms of proxy server hit ratio, byte hit ratio, mean response time and students quality of experience. Moreover, through the 360-degree panoramic VR football teaching videos learning, students can intuitively analyze the actions and improve the teaching quality. The reconstruction of football teaching environment is beneficial to promote the combination of football teaching and smart learning.

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APA

Li, H., Cui, C., & Jiang, S. (2024). Strategy for improving the football teaching quality by AI and metaverse-empowered in mobile internet environment. Wireless Networks, 30(5), 4343–4352. https://doi.org/10.1007/s11276-022-03000-1

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