Intelligent Monitoring System for the Elderly based on Posture Recognition

Abstract

 In recent years, due to the gradual increase in the elderly population, elderly care has become an increasingly urgent issue, and the most common risk faced by the elderly is accidental falls. In this paper, an intelligent monitoring system for the elderly is studied, which includes a communication module, a sensor module and a state detection module. It can monitor the status of the elderly in real time and feed back to the server to activate the buzzer alarm function. In the communication module, WI-FI communication between esp32 microcontroller and PC is established to realize real-time transmission of pressure sensor data. The C/S communication method between Raspberry PI and PC was established to realize the transmission of real-time video data. In the sensor module, the pressure sensor is used for data acquisition, and the RF algorithm is used to realize the binary classification prediction of whether the human body is in bed or out of bed. In the state detection module, the yolov8 algorithm combined with the GSRF algorithm is used to classify the image data into five action categories, namely, falling, waving, sitting, standing and walking, to predict the state of the human body in the real-time video stream with an accuracy of 90%. After the sensor module detects the state of the human body out of bed, the state detection module is started, and the results are transmitted back to the back-end server and uploaded to the Web page to realize the function of real-time monitoring of the state of the elderly.