The Application of Wireless Network-Based Artificial Intelligence Robots in Badminton Teaching and Training

Area of Science:

• Sports Science
• Robotics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly applied in sports for athlete training.
• Traditional badminton training methods can be complex and less efficient.
• Intelligent robots offer a potential solution for personalized and effective sports training.

Purpose of the Study:

• To investigate the application of AI-powered robots with wireless networking for badminton teaching and training.
• To develop and evaluate a system that trains athletes with preprogrammed moves and techniques.
• To compare the effectiveness of a proposed AI decision tree algorithm (DTA) against existing methods.

Main Methods:

• A system deploying intelligent robots connected via wireless networks for badminton training.
• Preprogramming various plays and player movements into the robots.
• Utilizing adjustable variables like speed, frequency, angle, height, and coordinates for training.
• Implementing the decision tree algorithm (DTA) for motion analysis and comparing it with the sports motion segmentation method (SMSM).

Main Results:

• The proposed AI robot system demonstrated improved efficiency over traditional training methods.
• The decision tree algorithm (DTA) achieved an accuracy of 93% in training analysis.
• The DTA showed superior performance compared to the existing sports motion segmentation method (SMSM).

Conclusions:

• AI-powered robots integrated with wireless networks offer a more efficient and accurate approach to badminton training.
• The decision tree algorithm (DTA) is a highly effective tool for analyzing and improving athlete movements in sports.
• This technology has the potential to revolutionize athlete development in sports like badminton.