Data acquisition and processing of body features of 24-style Taijiquan practitioners in mobile edge computing

This research delves into a detailed examination of the physical data from practitioners of 24-style Taijiquan, utilizing mobile edge computing (MEC). The aim is to aid the spread and growth of 24-style Taijiquan while broadening the use of MEC algorithms. Initially, the study focuses on understanding the architecture and progression of MEC, examining its strengths in gathering and processing data. Then, using MEC to analyze physical feature data, the study discusses the impact of 24-style Taijiquan on the human body, as well as the influence of MEC analysis results on the future promotion and development of 24-style Taijiquan. The research findings demonstrate that (1) mature MEC has significant advantages in data collection and processing; (2) a distributed computing system using edge devices can efficiently, low-energy, and quickly respond to body data, demonstrating the advantages of MEC in collecting and processing physical data of 24-style Taijiquan practitioners. These results underscore the efficacy of employing mobile edge computing (MEC) for the analysis of physical data from 24-style Taijiquan practitioners, thereby aiding in its preservation and advancement.