Applying Artificial Intelligence Technology to Analyze the Athletes’ Training Under Sports Training Monitoring System

IF 0.9 4区计算机科学 Q4 ROBOTICS

International Journal of Humanoid Robotics Pub Date : 2022-11-23 DOI:10.1142/s0219843622500177

Li Tan, Ningpei Ran

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Abstract

With the rapid development of artificial intelligence, the related technologies and applications that accompany it emerge as the times require. The industry based on artificial intelligence is booming. Image recognition and target tracking technology are widely used in various fields, especially in the fields of security monitoring and augmented reality. Combined with the characteristics of athletes’ sports, an auxiliary information system is developed to supervise and guide the training in real time. It can track and analyze the characteristics of individual athletes’ sports function, the arrangement of coaches’ training plan, the state of brain function, the index of routine physiology and biochemistry, nutrition regulation, and the condition of injuries and injuries in the middle of the day, so as to reveal the athletes’ training in the middle of the day the changing rule of various indexes in the training state. Based on the mobile artificial intelligence terminal technology, this paper develops and designs a monitoring system for athletes’ training process in C/S mode. GPS is used to obtain athletes’ position information in real time and provide real-time guidance for athletes.

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应用人工智能技术分析运动训练监控系统下的运动员训练

随着人工智能的快速发展，随之而来的相关技术和应用也应运而生。基于人工智能的产业正在蓬勃发展。图像识别和目标跟踪技术被广泛应用于各个领域，特别是在安防监控和增强现实领域。结合运动员运动特点，开发辅助信息系统，对训练进行实时监督和指导。可以对运动员个体运动功能特点、教练员训练计划安排、脑功能状态、日常生理生化指标、营养调节、伤伤状况等进行跟踪分析，从而揭示运动员中午训练中训练状态下各项指标的变化规律。本文基于移动人工智能终端技术，开发设计了一个C/S模式的运动员训练过程监控系统。利用GPS实时获取运动员的位置信息，为运动员提供实时指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Humanoid Robotics 工程技术-机器人学

CiteScore

3.50

自引率

13.30%

发文量

审稿时长

6 months

期刊介绍： The International Journal of Humanoid Robotics (IJHR) covers all subjects on the mind and body of humanoid robots. It is dedicated to advancing new theories, new techniques, and new implementations contributing to the successful achievement of future robots which not only imitate human beings, but also serve human beings. While IJHR encourages the contribution of original papers which are solidly grounded on proven theories or experimental procedures, the journal also encourages the contribution of innovative papers which venture into the new, frontier areas in robotics. Such papers need not necessarily demonstrate, in the early stages of research and development, the full potential of new findings on a physical or virtual robot. IJHR welcomes original papers in the following categories: Research papers, which disseminate scientific findings contributing to solving technical issues underlying the development of humanoid robots, or biologically-inspired robots, having multiple functionality related to either physical capabilities (i.e. motion) or mental capabilities (i.e. intelligence) Review articles, which describe, in non-technical terms, the latest in basic theories, principles, and algorithmic solutions Short articles (e.g. feature articles and dialogues), which discuss the latest significant achievements and the future trends in robotics R&D Papers on curriculum development in humanoid robot education Book reviews.