Social distance monitoring system using deep learning and entry control system for commercial application

For the last few months, the world has been under an astringent lockdown due to COVID-19. The number of COVID-19 cases is incrementing steadily. Even though scientists have found a vaccine for the obviation of the virus, the threat of being affected is high when we head out. Thus, one of the most efficacious modes of aversion is social distancing and home quarantine. As this was a sudden outbreak, people have not stocked up supplies and most of their personal work has been halted. Therefore, when people start to go outside, with or without a vaccine, it will be arduous to follow social distancing in countries, which are densely populated. With this in mind, this paper proposes a system that can be used in commercial spaces such as shops, banks, malls, offices, restaurants, and other similar places, where the system continuously checks whether customers are adhering to social distancing norms and only allows a certain number of people into the commercial space. This system is made up of two parts: an Entry Control System and a Six feet Apart analysis. This paper's work has been compared to previously completed projects and discussed. People who are concerned about social distancing and overcrowding will benefit greatly from the installation of this gadget in the private and/or public sectors.