Humanity is suffering greatly as a result of the coronavirus sickness, which appeared in 2020. Wearing a "Face Mask" in public and upholding "Social Distancing" are the only preventative measures we have against this pandemic. Additionally, a lot of service providers, including hotels, hospitals, train stations, and airports, require customers to use the service only if they appropriately wear the Mask and maintain social distance. Because it would take a lot of labor, it would be impossible to personally check people to see if they adhered to the social distance and mask requirement. In this paper, people are detected using pretrained Yolov3, and social distance violations are determined using Euclidean distance. Deep learning modules will be applied for face mask detection. Without a manual monitoring system, the system offers safety and security tools. It can be used in any hospital, office, public building, educational institution, work site, airport, etc. The proposed face mask and social distance detection system has the potential to be used to help assure individual and group safety if implemented properly.