Open AccessSmart SOP’s Surveillance System using Deep Neural Network
Author(s) -
Chaman Lal,
Zahid Ali,
Shagufta Aftab,
Suresh Kumar Beejal,
Mehwish Shaikh,
Ambreen Fatima
Publication year - 2022
Publication title -
international journal of current research and review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.112
H-Index - 4
eISSN - 2231-2196
pISSN - 0975-5241
DOI - 10.31782/ijcrr.2022.14705
Subject(s) - pandemic , face (sociological concept) , computer science , covid-19 , computer security , artificial intelligence , deep learning , internet privacy , medicine , disease , infectious disease (medical specialty) , social science , pathology , sociology
The global pandemic Corona virus sickness 2019 had a devastating impact on the world, according to statistics received by the World Health Organization. A study shows that about 33 million people are affected by the virus and more than 1 million deaths are reported worldwide. Currently, there are no specific vaccines or treatments for COVID-19. Now, WHO recommends that wearing a mask and following the SOP’s can help us in preventing the spread of the virus. There are only few studies about face mask detection based on image analysis. To create a safe environment in public places, educational institutions, & shopping malls we are proposed an effective idea based on computer vision and AI which is focused on real-time automated monitoring through the camera to detect people whether they are wearing a mask or not, also checks body temperature by the sensorbased model. In this proposed system modern deep learning algorithms have been mixed with different techniques to detect the unmasked faces and temperature and generate warning alerts by capturing images of the people not wearing masks and if the person has temperature, then it will also generate an alert of having temperature. This system favors society in preventing the spread of the virus as it has already infected 33 million people worldwide. The goal is to evaluate the face detection through image processing to prevent society from the spread of global pandemic disease and pollution.