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物联网结合无线网络技术在排球教学与训练中的应用。

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training.

机构信息

Department of Physical Education, Dongguan City College, Dongguan 523109, Guangdong, China.

Physical Education Department, Longcheng High School, Shenzhen 518106, Guangdong, China.

出版信息

Comput Intell Neurosci. 2022 Aug 10;2022:8840227. doi: 10.1155/2022/8840227. eCollection 2022.

Abstract

Motion information collection technology is a means for measuring, tracking, and recording the movement traces of individuals in space. This method can complete the data collection of volleyball players and the ball trajectory and realize quantification and statistical analysis of the data to present a virtual model of the player's movement trajectory. It is inseparable from the acquisition of information to complete the information collection. Therefore, this work uses the radio frequency identification (RFID) technology in the Internet of Things technology to build an information collection system and apply it to volleyball sports. The existing positioning system based on RFID has problems such as significant positioning errors and high system costs due to the arrangement of a large number of readers. This paper first introduces the theoretical knowledge of the RFID system, wireless network positioning technology, and RFID system positioning method in the Internet of Things. Besides, the theoretical framework of the volleyball movement information acquisition system is presented based on the Received Signal Strength Indication of the RFID system and Location Identification based on the Dynamic Active RFID Calibration (LANDMARC) algorithm. Then, the LANDMARC algorithm is improved through the Centroid Positioning algorithm, forming the CP-LANDMARC algorithm. Finally, a simulation experiment is conducted to test the system effect. The results demonstrate that: (1) the average error of the basic LANDMARC algorithm is 0.55 meters, and the average error of the CP-LANDMARC algorithm is 0.46 meters; (2) the average error of the CP-LANDMARC algorithm is 0.43 meters when the reference label is set to be evenly distributed in a square, and the average error of the optimized algorithm is 0.38 m when the reference label is set as an equilateral triangle; and (3) when the number of reference labels increases to 110, the average error decreases from 0.38 to 0.29. This paper aims to improve the quality of volleyball teaching and training by designing a relevant sports information acquisition system.

摘要

运动信息采集技术是测量、跟踪和记录个体在空间中运动轨迹的一种手段。这种方法可以完成排球运动员和球轨迹的数据采集,并实现数据的量化和统计分析,呈现出运动员运动轨迹的虚拟模型。完成信息采集离不开信息的获取,因此,本工作采用物联网技术中的射频识别(RFID)技术构建信息采集系统,并将其应用于排球运动中。现有的基于 RFID 的定位系统由于需要布置大量的阅读器,存在定位误差大、系统成本高等问题。本文首先介绍了 RFID 系统、无线网络定位技术和物联网中 RFID 系统定位方法的理论知识,提出了基于 RFID 系统的接收信号强度指示和基于动态主动 RFID 校准的位置识别(LANDMARC)算法的排球运动信息采集系统的理论框架。然后,通过质心定位算法对 LANDMARC 算法进行改进,形成 CP-LANDMARC 算法。最后,通过仿真实验对系统效果进行测试。结果表明:(1)基本 LANDMARC 算法的平均误差为 0.55 米,CP-LANDMARC 算法的平均误差为 0.46 米;(2)当参考标签均匀分布在正方形中时,CP-LANDMARC 算法的平均误差为 0.43 米,当参考标签设置为等边三角形时,优化算法的平均误差为 0.38 米;(3)当参考标签数量增加到 110 个时,平均误差从 0.38 降低到 0.29。本研究旨在通过设计相关的体育信息采集系统,提高排球教学和训练的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf75/9385343/5c9bf465ed6e/CIN2022-8840227.001.jpg

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