School of Physical Education, Chengdu Normal University, Chengdu 611130, Sichuan, China.
Comput Intell Neurosci. 2022 May 19;2022:1994046. doi: 10.1155/2022/1994046. eCollection 2022.
Since the reform and opening, China's economy has grown rapidly, and people's living standards have improved significantly. As one of the most effective ways to implement national fitness, square dance has gradually become the main lifestyle of urban communities, an important part of China's sports construction, and an important indicator to reflect the fitness of the masses and the construction of a well-off society in an all-round way. On the other hand, with the rapid development of internet of things technology, many people can use intelligent bracelets based on machine learning technology to realize motion detection. This technology is also applicable in square dance, which is of great significance to exercise and protect health. This paper first reviews the research status of the internet of things communication protocol and cloud platform, then introduces and analyzes the MQTT communication protocol and Netty high-performance network framework, and studies the integration technology of the internet of things and machine learning. Then, according to the characteristics of the internet of things, a scheme to realize data preprocessing is proposed. The value to be completed is calculated based on the correlation of other attributes corresponding to the k-nearest neighbor model (KNN) and the regression model. Finally, the machine learning algorithm is used to train the results of the three models to obtain the final filling value. The whole scheme design allows the machine learning algorithm to obtain relatively high-quality data in the internal environment. This paper designs a sports monitoring data system for square dance by combining machine learning and internet of things technology, so as to promote national fitness.
自改革开放以来，中国经济迅速发展，人民生活水平显著提高。广场舞作为实施全民健身的最有效手段之一，逐渐成为城市社区的主要生活方式，是中国体育建设的重要组成部分，也是全面反映群众健身和小康社会建设的重要指标。另一方面，随着物联网技术的快速发展，许多人可以使用基于机器学习技术的智能手环来实现运动检测。这项技术在广场舞中也具有重要意义，对锻炼和保护健康具有重要意义。本文首先回顾了物联网通信协议和云平台的研究现状，然后介绍和分析了 MQTT 通信协议和 Netty 高性能网络框架，并研究了物联网与机器学习的集成技术。然后，根据物联网的特点，提出了一种实现数据预处理的方案。根据 k-最近邻模型（KNN）和回归模型对应其他属性的相关性，计算要完成的值。最后，使用机器学习算法对三个模型的结果进行训练，得到最终的填充值。整个方案设计允许机器学习算法在内部环境中获得相对高质量的数据。本文通过结合机器学习和物联网技术，设计了一个广场舞运动监测数据系统，以促进全民健身。
