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Turkish Journal of Electrical Engineering and Computer Sciences

Authors

BIN ZHOUFollow

DOI

10.55730/1300-0632.4079

Abstract

Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node energy sensitivity, network distribution openness, data demand reliability, etc. Thus, the research on data security fusion method of the IoT has important theoretical significance and application prospects. In order to ensure the authenticity and reliability of the fusion results of physical fitness training data, the security characteristics and performance of the IoT are analyzed, and the basic requirements for the security fusion of IoT sensory data are identified. An improved cluster-based data fusion model is proposed to address the shortcomings of the cluster-based data fusion model, and a security fusion method of physical fitness training data is studied. Finally, this article conducts a large number of simulation experiments. The experimental results show that the improved cluster based data fusion model has better performance, further improving the security of physical fitness training data fusion based on the IoT. Finally, the article provides a security performance analysis.

Keywords

Data security fusion, physical fitness training, Internet of Things, improved cluster-based data fusion model

First Page

436

Last Page

451

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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