Implementation of the internet of things to help public awareness of the importance of using masks

Coronavirusi deasease 2019 or abbreviated as COVID-19 is an infectious disease that spreads very quickly. COVID-19 is caused by a new type of virus, namely Sars-CoV-2. In the situation of the increasingly widespread COVID-19 virus, many technology-based studies have examined an application to detect mask users to help raise public awareness of the importance of using masks to protect themselves or others. In this study, a prototype windows-based application called mask detector will be developed using the internet of things as an alarm medium, with the python programming language being used for programming languages. In the development of the mask detector prototype, the reference was taken from previous research that used the haar cascade classifier method but had a maximum detection distance of 180 cm. In this study, the main focus is the implementation of a mask detector application prototype that can be used at a distance of more than 180 cm from the user using the deep neural network method. By using the deep neural network method which is accompanied by the implementation of the internet of things, it is hoped that it can become literacy material and can improve some previous research.