Research on Personalized Learning in Physical Education Facilitated by the Integration of Artificial Intelligence and the Internet of Things

With the global rate of physical inactivity continuing to rise, the traditional "one-size-fits-all" model of physical education is unable to meet the diverse needs of students. This study explores the application of Artificial Intelligence (AI) and the Internet of Things (IoT) in promoting personalized learning in physical education, aiming to develop an integrated framework to enhance teaching efficiency and health outcomes. Through literature reviews and theoretical analysis, core concepts are defined, and a technical framework is constructed, including a closed-loop mechanism for data collection, analysis and decision-making, and feedback execution. The implementation of this framework in various scenarios, such as campus physical education classes, online education, training for special populations, and student competitions, is discussed. The study found that AI-IoT collaboration has the potential to increase student engagement, prevent sports injuries, and promote inclusive development, but faces challenges such as data privacy, algorithmic bias, and high costs, which can be mitigated through encryption protocols and teacher training. This framework has the potential to drive the transformation of physical education toward data-driven approaches and contribute to public health goals. Future recommendations include conducting empirical validation and expanding global applications to achieve a smart sports ecosystem.