COVID-19 Mandatory Self-Quarantine Monitoring System
Keywords:COVID-19, Mandatory Self-Quarantine System, Geolocation Tracking System, Face Recognition System
In response to rising COVID-19 cases, the Malaysia government imposed multiple measures to prevent virus transmission. Among the efforts taken by MoH were the enforcement of a-14 day self-quarantine for PUI, PUS and positive Covid-19 patients without symptoms to curb local transmission. However, the violations of self-quarantine are still being reported due to the location data of the users that cannot be tracked by the available system. Thus, this project proposes a system to monitor and track the self-quarantine PUI and PUS in real time by implementing geolocation tracking and face recognition. The geolocation tracking is developed to monitor users to stay in their quarantine place within 30 meters radius, and prevent unauthorized movement by scanning the users’ faces every two hours. User also requires updating their health status every day in the proposed system. If the user is classified as a very high risk dependent, admin and user will receive an alert notification for further action. The test result shows the developed map API can track multiple people with accuracy of 99% and the location of users can be displayed in real time in the map. In addition, the system can detect the user’s face accurately in various conditions within 1 second. As a result, this system could be used by the authority in order to reduce the self-quarantine violation rate in which subsequently help to prevent the spread of COVID-19.