Construction of a smart management system for physical health based on IoT and cloud computing with big data

Abstract In response to the needs of physical health data management in the context of the Internet of Everything, this article first uses cloud computing, big data, mobile Internet and other technologies to build a physical health smart management system. When the system is deployed, edge nodes are introduced in each data collection area, and the system is composed of data collection, transmission, and query and analysis modules. Secondly, it uses convolutional neural network to learn features from body measurement data unsupervised. Then, based on the Gaussian mixture distribution, a three-level physical fitness assessment model was established. Finally, input the learned features into the evaluation model to get the result of physical fitness evaluation. The results show that the system not only has a better response to the family, but also can reduce operating costs and improve work efficiency. Moreover, the algorithm in this paper is not affected by individual physical fitness assessment methods and results, and provides new ideas and methods for physical fitness assessment.