Research on Physical Health Monitoring and Management of University Students Based on Hadoop Swot

Abstract

With the rapid development of science and technology, information technology has gradually matured. The integration of a lot of complicated information has gradually spawned the technology of big data. Under the adjustment of relevant technicians, big data has also been applied in many fields. The government attaches great importance to the physical health of college students, and monitoring the development of college students’ physical health must be consistent with the concept of coconstruction, cogovernance, and sharing. In this article, advanced technologies such as cloud, Internet, mobile computer, and data fusion are applied to the products in the medical field. Under the basic principle of “patient-centered,” a digital and visual model is established. Through information technology, patients can realize limited medical treatment. The sharing of resources promotes the optimization of medical service processes. The method used in this article is big data analysis. Big data is widely used after high-performance analysis to achieve the purpose of reducing cost, shortening time, increasing artificial intelligence decision-making, and analysis trend accuracy. It can be concluded from the research in this article that the improved DCFA algorithm is used to optimize the SVM and the original FA algorithm to optimize the SVM algorithm for example verification, and the algorithm in this article is optimized by 35% compared with the traditional algorithm.