Tennis Mate - Multi-Function Tennis Training Equipment & Tennis Training Aids That Goes Easy On Your Tennis Traning.

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International Conference on Artificial Intelligence Human-Computer Interaction and Robotics (AlHCIR 2023) publish

Based on the research results of "Swallowsing Sports" Tennis mate @ Smart Training Equipment - 

Research on Accuracy Verification of an Intelligent Tennis Practicing Device Based on Stochastic Differential Equations 


Abstract of results: Taking the smart tennis equipment of Swallowsing Sports as the research object. By reading the data of simulated physical tennis ball, such as motion acceleration, angular velocity and tennis ball rotation speed, data selection and calculation are carried out to generate virtual three-dimensional tennis ball trajectory and drop point in the tennis court.

At the same time, according to the athletes' performance and training needs, the corresponding training guidance is provided to improve the training effect.

The research provides a new method and way for the design and accuracy verification of intelligent tennis trainer.

  

The paper points out that the intelligent tennis practice device has a built-in intelligent sensing module in the physical simulation tennis ball, including electronic components such as speedometer, tachometer and three-dimensional gyroscope, which is used for data acquisition and upload during practice; Analyze and process users to form individual data packets; In the user's mobile terminal data download, interface data, including training time, frequency, strength, technology, movement path three-dimensional trajectory simulation, to build an intelligent tennis practice device system.

Advanced sensor technology and algorithm are adopted to solve the problem of accuracy of data acquisition and stability of intelligent guidance.

Experimental data obtained:

In order to verify the accuracy and stability of the intelligent tennis player design based on stochastic differential equation, a series of experiments were carried out, and the results were statistically analyzed.

The researchers found that the trajectory of a tennis ball can be simulated effectively by constructing a stochastic differential equation model, and the accuracy of data feedback can be improved. Specifically, the researchers' algorithm achieved high accuracy in 25 sets of basic tennis actions, such as simulated serves, forehand and backhand low cuts, interceptions, flat shots, and volleys.

In the experiment, real tennis ball trajectory data were collected, including horizontal and vertical position information and speed information.

These data are fed into stochastic differential equation models for parameter estimation and numerical simulation. In addition, by comparing with the actual data, it is found that the applied algorithm has small deviation and high precision in predicting the landing location of tennis balls.

 

The study concluded:

In this study, a stochastic differential equation model is constructed to test the accuracy of the intelligent tennis player algorithm and improve the accuracy of data feedback. The experimental results show that the algorithm can effectively simulate the trajectory of tennis ball and predict the landing position.

At the same time, through the comparison with the actual data, it is found that the algorithm of the researcher has high accuracy and reliability.

In addition, the intelligent tennis practice device can also provide corresponding training guidance according to the athlete's performance and training needs to improve the training effect.

Therefore, the research results provide new methods and ideas for the design and accuracy verification of intelligent tennis devices.

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