Case study demonstrates improved teaching effectiveness in physical education through big data and AI, highlighting its potential for schools with limited IoT infrastructure.
This case study explores in depth the sports platform driven by big data and artificial intelligence (AI) in a certain university, aiming to solve the problems of uneven distribution of resources, lack of personalized teaching, and outdated evaluation system in traditional sports teaching. To meet these challenges, the authors have deployed a strong information technology (IT) infrastructure that integrates wearable devices, edge computing-based attitude estimation algorithms, and cloud analysis. This platform not only achieves automatic tracking and real-time feedback of student sports data but also provides personalized training suggestions, significantly improving the teaching effectiveness of physical education courses. Thanks to the edge computing architecture, the cost of cloud services has been reduced by 40%. Meanwhile, the modular design of the system enables it to be replicated and applied in school environments with weak internet of things (IoT) infrastructure, providing a technological pathway for other educational institutions to learn.
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Zhang et al. (2025) studied this question.
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