Detecting Presence of Masks and Violation of Social Distancing

Background:: 2020 brought an epidemic with it which already have taken a lot of live all around the globe. The vaccine of this disease named COVID-19 is still under trails but there are some precautionary measures issued by WHO for people to keep themselves safe from getting infected and transfer it forward. However, some people are not taking this seriously and due to that government has also issued some rules and regulations for people who are not following the precautionary measures. Methodology:: In this study, we worked on how to find defaulters in real time world and identifying them between the group of number of people and ask them to follow the precautionary measures and if necessary, take actions against them. A convolutional neural network model was created and was implemented in finding the defaulters from a group of people. Results:: The model worked quite well in identifying people with and without face masks and also whether the people are following social distancing or not simultaneously through the webcam. The model was able to detect multiple number of people at once and also calculate distance between them and checking whether they are wearing masks or not. Practical Applications:: The research can be used in various places like factories, shops, roads, and other public places. In the areas where a number of people are working together, during this time it has become a necessity to have precautions. But due to some people’s negligence it has become necessary for government bodies to keep check on these people and take necessary actions required and ensure the safety of others and also them. Therefore, it can used in surveillance system in the entire cities to keep check. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.