Abstract
Traditional athlete physique data monitoring systems are plagued by data processing delays, security vulnerabilities, and high operational costs, whereas the integration of edge computing and blockchain technology addresses these issues through real-time processing and data tamper-proofing. This paper designs a data monitoring IoT system combining edge computing and blockchain, elaborates on building digital models of asset objects such as devices, images, and applications through blockchain technology, and uses trusted edge platform design to protect Business data and device identity information. The research also explores the practical application of edge computing-based blockchain technology in data monitoring, including how to use edge computing to meet the computing needs of IoT applications and how to maintain the validity and connectivity of data in the blockchain. In the athlete physique data monitoring system, the experimental results show that the storage requirement of the master node in the athlete monitoring system is 42 GB, and the average size of each data block is 4.785 MB. The time delay of blockchain data processing is 4.96 s, and the real-time response rate of the overall system is improved by 16.2%. The monthly bandwidth usage of the master node is 598 GB and the compute resource consumption is 35,849 units (measured in processing units).
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