COVID-19 social distancing tracking and monitoring system (SDMOS-19)

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. According to the Ministry of
Health (MOH), by August 21, Malaysia has recorded 1.59 million COVID-19 cases and about 14,000 deaths. COVID-19 is an infectious disease that causes respiratory infections similar to the flu, and those infected exhibited symptoms such as a cough, fever, and, in extreme cases, breathing difficulties. The World Health Organization (WHO) declared COVID-19 an epidemic. Unfortunately, the virus mutates and continues spreading in the surroundings. According to recent research, the Omicron variant is highly transmissible and spreads more easily than the other variants, even among vaccinated individuals. As a precaution, individuals are advised to maintain a safe distance of five feet from one another during a social meeting. This study develops an automated social distancing detector system using the Convoiutionai Neural Network (CNN) algorithm using still images and recorded Closed-Circuit Television (CCTV) videos as the inputs. The system automatically measures and monitors the social distance between people in a crowded environment. The system detects human social distancing accurately and categorizes the distance between people as dangerous or safe using red and green bounding box
indicators. The results show that the system has a 90"/o detection accuracy. The proposed automated social distancing
detector system has promising potential for implementation in large premises such as shopping malls or recreational parks because it offers instant notification to the security department or other enforcement agencies whether the public adheres to the safe social distance requirement.