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

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yang Wen ◽  
Fangliang Yu
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Network Management ◽  
Sensor Network ◽  
Working Life ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Sports Events ◽  
Movement Ability ◽  
Multiagent Cooperation

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.

scholarly journals Sports Monitoring Method of National Sports Events Based on Wireless Sensor Network

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhongxiao Wang ◽  
Dong Zhu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Human Body ◽  
Life Experience ◽  
Real Life ◽  
Wireless Sensor ◽  
Residential Areas ◽  
Monitoring Method ◽  
Sports Events ◽  
Traditional Sports

Ethnic sports are various ethnic sports that have gradually evolved into various popular sports in the long-term life experience, according to different living habits and residential areas, in the hunting activities of similar sports in the past. Based on the use of wireless sensor networks, this paper monitors the traditional national sports activities, provides real-time feedback on the actual human body conditions in different sports, and finds out the pros and cons of traditional sports and makes improvements. The object proposes a national automated monitoring test, which uses several small sensors in the wireless sensor network to transmit information to monitor many real conditions in the human body during multisport, so as to find out that the national sports exercise is in real life. Experimental results show that in recent years, all ethnic groups have attached great importance to ethnic sports. The 11th Ethnic Minority Games held in 2019 will have 18 competitions, 17 individual events, 131 small events, and 55 ethnic minorities that participated in the joint participation of more than 7000 athletes participating in traditional sports of all nationalities and are the best inheritance and development of national sports.

Routing Using Genetic Algorithm in a Wireless Sensor Network

2020 ◽  
Vol 111 (4) ◽  
pp. 2703-2732 ◽  
Author(s):  
Naveen Muruganantham ◽  
Hosam El-Ocla
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor

scholarly journals Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network

2019 ◽  
Vol 15 (8) ◽  
pp. 155014771986987 ◽  
Author(s):  
Zhanjun Hao ◽  
Nanjiang Qu ◽  
Xiaochao Dang ◽  
Jiaojiao Hou
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Particle Swarm Optimization Algorithm ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Swarm Optimization ◽  
Passive Monitoring ◽  
Link Model

3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.

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