Open AccessCOVID Safety Measures Alert System
Author(s) -
D. Gayatri Devi
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.36288
Subject(s) - computer science , python (programming language) , face (sociological concept) , artificial intelligence , covid-19 , face detection , computer vision , facial recognition system , social distance , object class detection , pandemic , pattern recognition (psychology) , medicine , infectious disease (medical specialty) , social science , disease , pathology , sociology , operating system
The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection method is wearing a face mask and maintaining social distance in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports Indicate that wearing facemasks and maintaining social distance while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. So we are doing a Project on detecting whether a person wears a mask or not, also giving an alert message to the person to wear a mask, and maintain social distance or not. A hybrid model using deep and classical machine learning for face mask detection will be presented for face mask detection, a face recognition model is used to identify faces and an object detection algorithm is used to identify persons and also calculate social distance between each other. We collected face mask detection dataset consisting of mask and without mask images, and person photos to identify the person. We are going to use OpenCV to do real-time face detection from a live stream via our webcam. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and TensorFlow and Keras, use a face recognition module to identify faces and a YOLO algorithm to detect objects and calculate social distance. Our goal is to identify whether the person on a video stream is wearing a face mask or not, if not give an alert message to wear a mask and check for social distance between each other with the help of computer vision and deep learning.