Artificial Intelligence System for College Students’ Physical Fitness and Health Management Based on Physical Measurement Big Data

• Published in: Wireless communications and mobile computing Vol. 2021; no. 1
• Main Author: Ai, Li
• Format: Journal Article
• Language: English
• Published: Oxford Hindawi 2021; Hindawi Limited
• Subjects: Applications programs; Artificial intelligence; Bluetooth; Chronic illnesses; Colleges & universities; Data base management systems; Data collection; Data storage; Data warehouses; Disease prevention; Health care; Health care facilities; Health risk assessment; Health risks; Internet; Lifestyles; Medical research; Medical technology; Medical treatment; Mobile computing; Multidimensional data; Personal health; Physical fitness; Quality of life; Relational data bases; Research centers; Respiratory diseases; Risk assessment; Risk factors; Software development; Standard data; Students; United States > US; China; Japan
• ISSN: 1530-8669; 1530-8677
• DOI: 10.1155/2021/4727340

Most of the current health management products are used in medical institutions and generally do not pay enough attention to the student population. Based on this, this paper designs a student-oriented and functional autonomous health management system. This paper proposes a personal health management system based on a multidimensional data model based on the main social characteristics of the population with chronic diseases and the actual needs of personal health management for chronic diseases. The value of various health data for health management is deeply analyzed and mined, and a multidimensional model data warehouse is constructed according to relevant national health data standards to create a standard data platform for intelligent health warning and disease risk assessment. This paper researches and designs a closed-loop personal health management method based on the Plan-Do-Check-Action (PDCA) cycle management model, with detailed functional design in four aspects: health data collection and recording, health assessment, health planning, and tracking and execution. This paper researches health data collection, processing, and storage technologies and adopts HDFS data storage technology, html, css, Java Script, java, and other software development technologies, combined with j Query, UEditor, Date Range Picker, and other plug-ins, as well as SMS email generation interface, wireless Bluetooth transmission interface, etc. This system web and mobile application platforms are designed and developed. Relational database is used as the system database, and a snowflake-type multidimensional data model is designed. Finally, the functions and performance of this system were tested, and the development and trial run of the basic version have been completed.