Construction of Wireless Underground Footwork Mobile Training and Monitoring Sensor Network in Venues of Major Sports Events

Author:

Wen Yang12,Yu Fangliang23ORCID

Affiliation:

1. College of Sports Industry and Leisure, Nanjing Sport Institute, Nanjing 210014, China

2. Center of Jiangsu Sports Health Engineering Collaborative Innovation, Nanjing Sport Institute, Nanjing 210014, China

3. School of Sports Training, Nanjing Sport Institute, Nanjing 210014, China

Abstract

At the Summer Olympics in Tokyo, technology was used extensively in major sports events. The level of foot movement ability greatly affects the performance of sports technology. Modern sports are developing in the direction of high speed, high skills, flexibility, and rapidity, and more and more reflect the important position of reasonable and accurate foot movement ability in sports. This article uses wireless sensor technology and wireless communication technology to design the overall architecture of the wireless underground footwork mobile training and monitoring network in venues of major sports events. According to the determined monitoring parameters and data transmission plan, a wireless remote monitoring data acquisition system is designed, and the hardware design, software design, and networking of the wireless monitoring node are completed, so as to realize the real-time monitoring and remote transmission of the underlying data. This paper proposes a wireless sensor network management architecture and method based on multiagent cooperation and combines active and passive wireless underground footwork mobile training and monitoring for experimental verification. A multitask allocation strategy optimized for network working life is proposed. A genetic algorithm is used to model and optimize the task data report routing of cluster head nodes. The simulation experiment results show that the wireless sensor network management method based on multiagent cooperation can effectively coordinate different monitoring sensor nodes to complete the assigned monitoring tasks; the multitask assignment strategy based on a genetic algorithm can optimize the working life of the application network.

Funder

National Social Science Foundation of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering

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