According to data obtained by the World Health Organization, the global pandemic of COVID-19 has severely
impacted the world and has now infected more than eight million people worldwide. Wearing face masks and following safe
social distancing are two of the enhanced safety protocols need to be followed in public places in order to prevent the spread of
the virus. To create safe environment that contributes to public safety, we propose an efficient computer vision based approach
focused on the real-time automated monitoring of people to detect both safe social distancing and face masks in public places by
implementing the model on raspberry pi4 to monitor activity and detect violations through camera. After detection of breach,
the raspberry pi4 sends alert signal to control center at state police headquarters and also give alarm to public. In this proposed
system modern deep learning algorithm have been mixed with geometric techniques for building a robust modal which covers
three aspects of detection.
