Table tennis exercise system based on active radio frequency tag reading positioning

Abstract

The invention relates to a table tennis exercise system based on active radio frequency tag reading positioning. The system consists of a table tennis table, a table tennis net, table tennis bats, a table tennis ball and a server, wherein the table tennis table is provided with an active radio frequency tag reader; the table tennis net is provided with another active radio frequency tag reader; the table tennis bats are provided with pressure sensors; the table tennis ball is provided with an active radio frequency tag; the server is used for calculating positions according to the active radiofrequency tag; the active radio frequency tag readers on the table tennis table and the table tennis net are used for acquiring radio frequency signals transmitted from the table tennis ball with theactive radio frequency tag, used for receiving signal receiving start moments, and used for transmitting the signal receiving start moments to the server for calculating the positions according to the active radio frequency tag; the pressure sensors on the bat surfaces are used for acquiring pressure sensation data, and used for transmitting data of the pressure sensors to the server for calculating the positions according to the active radio frequency tag. By adopting the table tennis exercise system, the problem that a conventional table tennis exercise system based on Internet of Things has no function of calculating the position of the table tennis ball in real time is solved.

Description

technical field [0001] The invention belongs to the technical field of intelligent table tennis, in particular to a table tennis system based on active radio frequency tag reading and positioning. Background technique [0002] At present, there are two main types of technologies for monitoring table tennis, one is computer vision analysis method, and the other is signal trigger judgment method. [0003] The computer vision analysis method mainly uses multiple high-speed high-definition cameras to collect real-time videos of table tennis in motion, and performs target recognition and spatial positioning on each image in the video to form data, and then calculates the trajectory of the table tennis ball through filtering and tracking. The disadvantage is that the calculation complexity is high and the performance requirements of the equipment are high. [0004] The signal trigger judgment method is to obtain the signal generated by the impact of the table tennis ball through ...

AI Technical Summary

Problems solved by technology

[0003] The computer vision analysis method mainly uses multiple high-speed high-definition cameras to collect real-time videos of table tennis in motion, and performs target recognition and spatial positioning on each image in the video to form data, and then calculates the trajectory of the table tennis ball through filtering and tracking. The disadvantage is that the calculation complexity is high and the performance requirements of the equipment are high

[0004] The signal trigger judgment method is to obtain the signal generated by the impact of the table tennis ball through the piezoelectric sensor installed on the table tennis table and the ball net, compare the strength and generation time of multiple signals, and calculate the impact position and approximate trajectory of the table tennis ball , the disadvantage of this scheme is that it cannot locate the position of the table tennis ball in the air, and the positioning accuracy is low

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