Health Monitoring at Home using Deep Transfer Learning

Abstract

During certain situations, the healthcare system is put under extreme pressure. Isolated non-critical infected patients may benefit from receiving health care services in their homes and can have the comfort, as this can reduce their burden and their stress levels. For this process keeping tabs on at home seniors health related activities is another important application. In this paper, we mention about a home health monitoring system based on transfer learning that uses an edge computing approach. In particular, edge devices may be used to train a model based on a pre-trained convolutional neural network using just a minimum quantity of data that has been tagged on the ground and a fine-tuning technique. Hence, there is no need to transmit the raw data picked up by these sensors to an external source. That is why you will not have to worry about any kind of data leakage, insecurity, or bandwidth scarcity. Moreover, real-time computation for the above mentioned works costs should be affordable. An AI-enabled health monitoring system, a computer vision system, the COVID-19 epidemic, deep learning, computing, transfer learning, and visual sensors are some of the terms that may be used to describe this system.