Mask aware: IoT for facemask detection and monitoring / Siti Nurfatin Mohtar and Aznoora Osman - Mohtar, Siti Nurfatin; Osman, Aznoora (College of Computing, Informatics and Media, UiTM Perlis, 2023)
Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Most people infected with the virus will experience mild to moderate respiratory illness and recover without requiring special treatment. This pandemic unexpectedly broke out in 2019 and has seriously affected the whole world. COVID-19 has infected more than 500 million people worldwide and caused over 6 million deaths. Malaysia has entered the endemic phase, the wearing of facemasks is not mandatory in public but still encouraged while using public transports such as bus, train, taxis, airplane, e-hailing vehicles as well as in hospital and medical institutions. Awareness is diminished as some places do not require the wearing of face masks. The government has given flexibility and no longer imposes actions on individuals. Therefore, the purpose of this study is to provide a way to give some awareness of the requirement for a face mask when handling with high-risk groups. This project will detect a mask by adjusting the mask to cover the mouth, nose, and chin. If no face mask is detected or not being worn properly, a message will be displayed to notify the person and a notification via Telegram will be sent to the authorize people. By having this project, the spread can be reduced, and we can be vigilant.