Automatic Social Distance Monitoring system using Deep Learning Algorithms

Abstract

In recent months, the worldwide outbreak of Corona Virus Disease (COVID-19) has created a panic situation for all human beings irrespective of the geographic location and economic status of the countries. The communal spread of the deadly virus can be prevented by maintaining the social distance between people and the wearing of face masks. This paper provides a prominent solution for monitoring using the Open-Source Computer Vision Library (Open-CV) and Deep Learning Algorithm to course people in public areas and to avoid crowding. This proposed project can be implemented using images taken from the Closed Circuit Television (CCTV). The distance between the people is detected with help of an object detection algorithm. The Euclidean distance is calculated and compared with the standard distance given. The persons with enough distance will be indicated in the green-colored bounding box and others with a red-colored bounding box. The total number of violations is also shown at the output feed. This project provides a solution to eradicate the spread of the deadly virus to an extent with minimum human effort and reduced risk of infection to the local athourities.