Leveraging Deep Learning and IoT for Monitoring COVID19 Safety Guidelines Within College Campus

Communications in Computer and Information Science - Advanced Computing ◽

10.1007/978-981-16-0401-0_3 ◽

2021 ◽

pp. 31-53

Author(s):

Sahai Vedant ◽

D’Costa Jason ◽

Srivastava Mayank ◽

Mehra Mahendra ◽

Kalbande Dhananjay

Keyword(s):

Deep Learning ◽

College Campus ◽

Safety Guidelines

Download Full-text

Deep Learning based Safe Social Distancing and Face Mask Detection in Public Areas for COVID-19 Safety Guidelines Adherence

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2020.30560 ◽

2020 ◽

Vol 8 (7) ◽

pp. 1368-1375

Author(s):

Shashi Yadav

Keyword(s):

Deep Learning ◽

Face Mask ◽

Social Distancing ◽

Public Areas ◽

Guidelines Adherence ◽

Safety Guidelines

Download Full-text

Face Mask Detection System using Deep Learning

International Journal for Modern Trends in Science and Technology - RTT2020 ◽

10.46501/ijmtst061231 ◽

2020 ◽

Vol 6 (12) ◽

pp. 161-164

Author(s):

Pinki and Prof. Sachin Garg

Keyword(s):

Deep Learning ◽

Large Scale ◽

Learning Algorithm ◽

Detection System ◽

Face Mask ◽

Video Stream ◽

Public Places ◽

Railway Stations ◽

Deep Learning Algorithm ◽

Safety Guidelines

In the present scenario due to Covid-19, there is no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed. To identify the person on image/video stream wearing face mask or not. If the person doesn’t wear a mask, the notification will be sent to the respected admin with the help of Python and deep learning algorithm by using the Convolutional Neural Network, Keras Framework and OpenCV.

Download Full-text