Social Distancing and Face Mask Detection using GoogleNet

According to statistics bought by using the World Health Organization, the world pandemic of COVID-19 has severely impacted the World and has now contaminated greater than 8,000,000 human beings worldwide. Wear face masks and to follow the protocols for safe social distancing maintenance are the security rules that want to be observed in public locations to prevent human beings from the spread of the virus. To develop safeguarded surroundings with COVID-19 free cases that contribute to the safety of the people, we propose a computer visionbased an environment-friendly method that aims the monitoring human beings in real-time in public locations to detect face masks on people's faces and social distancing in a safe manner by implementing the model which will monitor real- time activities of humans and detect breakage of rules through the camera. After detection of the breach, the system generates a red alert or alarm to prevent contact between humans.