基于物联网的体育教学智能监测与分析

Intelligent monitoring and analysis of physical education teaching based on internet of things

在体育训练中,如何科学化的根据人体的生理负荷实时、准确、有效地调节和控制体能负荷强度,使之与训练计划的预定目标相一致,是一个探讨很久的话题。随着当前物联网技术的发展,通过智能传感器可以收集到很多运动员数据。因此,为了更加准确地评估人体各项指标,提出一种基于机器学习的体测评估算法,通过利用BP网络的粒子群优化方法建立运动员身体状况的评价模型。实验结果表明,提出的算法具有较好的性能,能够满足实际需求。

In sports training,how to scientifically adjust and control the physical load intensity in real time,and how to accurately and effectively the physiological load in the human body to make it consistent with the predetermined goal of the training plan is a long-discussed topic.With the development of the current Internet of Things technology,a lot of athlete data can be collected through smart sensors.Therefore,in order to evaluate various indicators of the human body more accurately,a physical measurement evaluation algorithm based on machine learning is proposed here,and an evaluation model of the athlete's physical condition is established by using the particle swarm optimization method of the BP network.Experiment results show that the proposed algorithm has better performance and can meet actual needs.