The Internet of Things (IoT) and artificial intelligence (AI) have promoted teaching reform while improving people’s lives. Under the new teaching environment, the position of physical education (PE) teaching in the teaching work has become increasingly prominent. At present, there are some problems in the PE teaching mode of most colleges and universities, such as poor teaching environment, unstable teaching data, and lack of technical support for the teaching system. This also leads to the low quality of PE teaching and unsatisfactory teaching results. In this paper, IoT and AI are combined to study the application mode of innovative practical teaching in college PE. This paper first constructs a physical education teaching system based on the Internet of Things, then summarizes the necessity of artificial intelligence technology participating in the reform of physical education classroom teaching, and gives a specific teaching application model. Finally, based on the golden sine algorithm-optimization neural network, the application model of college physical education in this paper is evaluated. Through experiments and investigations, the new teaching mode improves the teaching efficiency by 14.7%, improves the teaching quality, and provides reference for the next development of IoT and AI in teaching.
New energy composite is an advanced material that can replace the traditional single metal material, especially the newly developed or developed material with superior performance. At present, the material is widely used in automobile manufacturing and other fields, but there is a lack of development and application of the material in the field of sports. To solve these problems, this paper puts forward the application of new energy composites in sports facilities and fitness equipment. In this paper, the testing methods of new energy materials, including thermoelectric testing method and energy absorption testing method, can quantitatively evaluate the properties of a kind of new energy composites and point out the direction for the development of materials with high thermoelectric properties and high-energy absorption and consumption properties. Then, through the preparation experiment of new energy materials, this paper studies the preparation process and self-shrinkage test of carbon nanomaterials. Finally, it is proposed to use carbon nanomaterials in the sensor design of health monitoring data acquisition system. The experimental results show that when the water ash ratio is low, the self-shrinkage value of carbon nanomaterial slurry is 74.68% lower than that under the original conditions. In the experimental study of omnidirectional monitoring characteristics, through the repeated tensile tests of rectangular sensor and omnidirectional sensor at different temperatures, it is found that the sensitivity coefficient of the sensor made of carbon nanomaterial is between 55.8 and 60.4, and the maximum fluctuation is only 5. This fully proves that the carbon nanotube omnidirectional sensor has omnidirectional detection ability.
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