The Worst Possible Situation Faced By Humanity, COVID-19, Is Proliferating Across More Than 180 Countries And About 37,000,000 Confirmed Cases, Along With 1,000,000 Deaths Worldwide As Of October 2020. The Absence Of Any Medical And Strategic Expertise Is A Colossal Problem, And Lack Of Immunity Against It Increases The Risk Of Being Affected By The Virus. Since The Absence Of A Vaccine Is An Issue, Social Spacing And Face Covering Are Primary Precautionary Methods Apt In This Situation. This Study Proposes Automation With A Deep Learning Framework For Monitoring Social Distancing Using Surveillance Video Footage And Face Mask Detection In Public And Crowded Places As A Mandatory Rule Set For Pandemic Terms Using Computer Vision. The Paper Proposes A Framework Is Based On YOLO Object Detection Model To Define The Background And Human Beings With Bounding Boxes And Assigned Identifications. In The Same Framework, A Trained Module Checks For Any Unmasked Individual. The Automation Will Give Useful Data And Understanding For The Pandemic’s Current Evaluation; This Data Will Help Analyse The Individuals Who Do Not Follow Health Protocol Norms.
