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

  • Published In: International Journal of Humanoid Robotics, 2023, v. 20, n. 6. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Tan, Li; Ran, Ningpei 3 of 3

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. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Humanoid Robotics. 2023/12, Vol. 20, Issue 6, p1
  • Document Type:Article
  • Subject Area:Sports and Leisure
  • Publication Date:2023
  • ISSN:02198436
  • DOI:10.1142/S0219843622500177
  • Accession Number:173469360
  • Copyright Statement:Copyright of International Journal of Humanoid Robotics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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