Research Area:  Wireless Sensor Networks
In conventional sports training, coaches record and observe athletes sports data and judge whether it is reasonable based on their own experience. This qualitative analysis method is highly subjective, has large errors, and is susceptible to interference. To solve the above problems, the design of the sports training system under the wireless sensor network and the research of movement monitoring and recognition become very important. This article aims to study the design of sports training system and the monitoring and recognition of actions under the wireless sensor network technology. This paper simulates the implementation of the proposed data collection protocol and the two basic protocols, the direct transfer algorithm and the flooding algorithm, and compares the protocol proposed in this paper with the other two algorithms in terms of average information transmission success rate and average network overhead. Among them, the average information transmission success rate represents the ratio of the number of messages successfully arriving at the base station to the total amount of information generated by all nodes, and the average network overhead represents the average number of messages sent by each node. Experimental results show that the data collection protocol proposed in this paper can dynamically provide different transmission qualities for information of different importance levels, effectively reducing network overhead, and the reduced overhead is 11 percent of the original.
Author(s) Name:  Yue Jia
Journal name:  Artificial Intelligence and Edge Computing in Mobile Information Systems
Publisher name:  Hindawi
Paper Link:   https://www.hindawi.com/journals/misy/2021/3104772/