IOT Based Primary Monitoring System for Covid-19

Abstract

The quick wide spread of COVID-19 - Coronavirus Disease 2019 has led us to a pandemic all over the world. The most important aspect to control this infectious outbreak is to ensure the correctness of wearing a facemask, but the advantage of facemasks are getting declined because of improper wearing. Throughout this study, we developed a new facemask-wearing status identification method through convolutional neural network and temperature sensing without any physical contact. The proposed algorithm is implemented in Raspberry pi module with a contactless temperature sensor to monitor a person’s temperature and as of facemask-wearing status is concerned, it involves three main steps as: pre-processing the image, detection of face and identification of facemask-wearing status. Our findings highlights the high level of accuracy in identifying the facemask-wearing status which can be accomplished by this proposed CNN, which can act as an important application in this pandemic prevention involving COVID-19. It also uses GSM technology to alert the status of person to avoid spreading of COVID-19.