• Akshada Bhalerao
• Shruti Bhalerao
• Vaishnavi Borgaonkar
• Rajshekhar Nandargi
• Bhakti Walimbe

Social distancing is a mandatory safety measure taken in order to have more control over the breakout of spreading diseases such as COVID-19. The coronavirus disease 2019 has brought global crisis with its deadly spread. Many scientists, healthcare organisations are working for proper medicines to cure this virus. For now, social distancing is the feasible approach to fight against this pandemic. The risks of virus spread can be reduced by avoiding physical contact among humans. It will focus on reducing the physical contact between possibly infected individuals and healthy persons, it can perform a very important role in overcoming the virus spread. The proposed system will be an efficient deep learning-based system to ease the process of monitoring the social distancing via human detection and distance finding approaches, where each individual is identified in video with the help of bounding boxes. For human detection, the CNN will be used to detect people and geometric difference is used to find the distance between two persons. In the proposed system if social distancing norms are not followed then indication will be given by changing the colour of the bounding box.

Deep Learning, Covid 19, Social-distancing, public-safety, YOLO v3, Geometric difference.

"Social Distance Monitoring System for Covid-19 based on Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.396-399, August-2022, Available :http://www.jetir.org/papers/JETIRFP06068.pdf

"Social Distance Monitoring System for Covid-19 based on Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. pp396-399, August-2022, Available at : http://www.jetir.org/papers/JETIRFP06068.pdf