Preventing Against Virus Transmission by Detecting Facemask for Gateway Operation System

ABSTRACT

The COVID-19 epidemic compelled régimes around the globe to enact quarantine in order to protect the virus from transmitting. According to the documentation, wearing a face mask at work minimizes the chance of spreading. Use of AI to provide an innocuous milieu in a production setup that is both efficient and cost-effective. Face mask detection will be enabled utilizing a mixed model combining machine learning and deep learning. We will utilize Open CV to do real-time face detection from a live feed through our camera using a face mask detection library that comprises of photos with and without a mask. In this work, this dataset is utilized to create a COVID-19 face mask detector with CV utilizing Open CV, Python, Tensor Flow, and other tools. The mail aim of the work is to find whether the being on the image/cinematic rivulet is exhausting a face mask or not through the aid of deep learning and computer revelation. By using this face mask detection, we are going to make a gateway system. This system allows people in only if they wear a face mask. We use Raspberry pi to make this system and an a4899 driver module to control the stepper motor. The gateway is controlled by the motor which is connected to the driver module. © 2021 IEEE.