Design and Implementation of An Intelligent Health Management System for Nursing Homes

Abstract

The ageing population has led to a dramatic increase in the demand for analysis and assessment of the health of older persons in public health services. Due to medical conditions and other reasons, most of the elderly in some urban nursing homes will only detect and analyze their own physiological indicators when they are sick. From the perspective of health management, we should continuously monitor the physiological indicators of each elderly individual, and through the analysis and evaluation of their daily physiological indicators data, and then predict and timely intervene in their health. This can not only effectively improve the health of the elderly, but also effectively reduce the pressure on public health services. In order to allow more elderly people in nursing homes to enjoy effective health monitoring and early warning and timely intervention, we have designed an intelligent health management system based on technologies such as cloud computing, Internet of Things, knowledge graph, and deep learning. The system consists of three parts: the Internet of Things platform, the intelligent analysis platform, and the SAAS management platform. The IoT platform is mainly responsible for collecting data such as daily physiological indicators, sleep data, air indicators, and service demands of elderly people in nursing homes. The intelligent analysis platform is mainly responsible for analyzing and evaluating the data collected by the IoT platform based on the disease knowledge map and related deep learning frameworks. The SAAS management platform is mainly responsible for background management and health data visualization on the nursing terminal, service terminal, and health monitoring terminal. The system realizes continuous monitoring, analysis, assessment, prediction and early intervention of the health of each elderly person in the nursing home, which effectively improves the health of the elderly and effectively reduces the pressure on public health services.