Intelligent soccer system based on biosensor network technology. (March 2021)

• Record Type: Journal Article
• Authors: Wang, Yang; Mao, Huaqing
• Is Part Of: Measurement. Volume 173(2021)
• Publication Date: 2021-03
• Subjects: MEMS Sensor -- Motion track -- Detection system -- Mobile sensor -- Network technology; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.108564
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Combined with the sequence of the data processing steps in the football track detection system. Effectively transform the football sensor data from the main coordinate system. The adaptive compensation algorithm based on zero state can eliminate the accumulated errors. Abstract: With the development of MEMS technology, mobile sensors have been used in people's daily life. In dynamic hazardous environments, mobile sensors can replace people to perform tracking and monitoring tasks in the field. The purpose of this paper is to study the design of intelligent soccer system based on biosensor network technology. Based on the research of the basic principle of sensor node location and the common methods of node location, an intelligent soccer trajectory detection system based on MEMS sensor is designed. The main content of this article is the trajectory detection system of the smart football in space based on the MEMS sensor integrated in the current smart football. The system is mainly used in the field of human-computer interaction to capture the actions of the human body by detecting the trajectory of football. Secondly, it can be used in some observation fields, such as GPS positioning accuracy compensation, short-distance ranging, etc. Therefore, in the process of studying the football trajectory measurement system, how to eliminate the errors in the system and improve the accuracy of trajectory detection is the focus of this paper. The experimental results show that by integrating the acceleration data collected before the motion at rest, the displacement can be obtained as 2194 cm. It can be seen that when the errors in the data are accumulated, the impact on the operation results of the system is very huge. The average error of 60 cm distance measurement is only 0.07%, and the average error of 600 cm distance measurement is reduced from 118.78% to 8.24%. It can be seen from the experimental data that the error processing scheme of the soccer track detection system designed in this paper has a significant effect on error compensation.