Design and Implementation of Sports Fitness Testing Equipment Based on Knowledge Graph Structure Optimization Algorithm

With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve their physical fitness through physical exercise. However, nowadays, the accuracy of sports quality measurement equipment is not enough. I...

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Veröffentlicht in:2023 International Conference on Data Science and Network Security (ICDSNS) S. 1 - 5
Hauptverfasser: Kong, Fanrong, Li, Guangpeng, Zhou, Hengchao
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 28.07.2023
Schlagworte:
Calibration
Data processing
Data science
Health and safety
knowledge graph
Knowledge graphs
Motion measurement
Network security
physical fitness
structural optimization
testing equipment
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Zusammenfassung:With the development of the times and the progress of society, people's attention to sports has become increasingly high. People hope to effectively improve their physical fitness through physical exercise. However, nowadays, the accuracy of sports quality measurement equipment is not enough. If the accuracy of sports quality measurement equipment is high, it can accurately record changes in people's physical fitness Therefore, this article focused on the design and implementation of sports quality measurement equipment based on knowledge graph structure optimization algorithms, aiming to improve accuracy through better design. The experimental test in this article used the knowledge graph structure algorithm to achieve a device accuracy of up to 88%, while the traditional device accuracy was up to 75%. The accuracy of traditional motion quality measurement equipment is the highest, at 75%, and the lowest, at 70%. Therefore, the knowledge graph structure algorithm can play a good role in sports quality measurement equipment.
DOI:10.1109/ICDSNS58469.2023.10245453