Temperature and Face Mask Detection with Contactless Sanitizer Dispenser

Abstract

Abstract: Face mask identification is suggested since it has been evolving quickly since COVID-19 insisted on it last yearfor its many uses in the field of Law Enforcement Security purposes and other commercial uses. The provided system uses a convolution neural network to assist in face mask identification utilising the COVID-19 security measure in both photos and videos. The performance evaluation of the suggested strategies is presented in this study along with a large-scale experiment on the data. The project serves as a prototype for temperature detection and face mask identification for humans. The first techniqueuses a temperature sensor to determine the body's current temperature and then evenly distribute sanitizer. The goal of the next strategy is to provide people with a safety net so that COVID-19 cannot spread among them. The suggested method conducts a thorough experimentation on 50 different Image datasets to look at performance. For ten random trails, the author experimented with different training and testing percentages. The findings indicate that the symbolic method is superior than the traditional approach.