In recent years, the increasing demand for physical health promotes the basketball sports industry’s reform. The latest science and technology enter the sports industry one after another and constantly impact the traditional sports equipment. However, the conventional sports technology scheme is unreasonable, and the sports training management models are obsolete. So, it is impossible to use scientific methods in basketball training, and the overall training effect is not good. This paper proposes a basketball training algorithm using big data and the Internet of Things. The proposed algorithm uses gesture recognition from continuous video movement characteristics of key figures, trajectory characteristics, and background information fusion. It improves the recognition mechanism based on the Shuangliu C3D video basketball player action classification method. Due to the lack of a scientific exercise plan for basketball players, a training plan based on BMI and IoT-enabled big data is devised. The proposed scheme is implemented so that different basketball players customize their own scientific sports training modules.

中文翻译：

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基于大数据和物联网的篮球训练应用算法

近年来，对身体健康的需求不断增长，推动了篮球运动行业的改革。最新科技相继进入体育产业，并不断冲击传统体育器材。然而，传统的运动技术方案是不合理的，并且运动训练管理模型已经过时。因此，不可能在篮球训练中使用科学的方法，总体训练效果不好。本文提出了一种利用大数据和物联网的篮球训练算法。所提出的算法从关键人物的连续视频运动特征，轨迹特征和背景信息融合中使用手势识别。它改进了基于双流C3D视频篮球运动员动作分类方法的识别机制。由于缺乏针对篮球运动员的科学锻炼计划，因此制定了基于BMI和基于IoT的大数据的培训计划。实施提议的方案，以便不同的篮球运动员定制他们自己的科学运动训练模块。