Abstract
With the arrival of Covid-19, several preventive measures were implemented to limit the spread of this virus. Among these measures is the use of masks, both in open and closed public spaces. This measure has forced commercial establishments, workplaces, schools, hospitals, to maintain constant vigilance, upon entering their facilities, of the proper use of the mask, which should completely cover the nose, mouth and chin. However, this manual control is tedious and ineffective since most of the population is not able to correctly identify when a person has the mask on properly, with high error rates in the manual detection of the correct use of the mask according to surveys carried out. For this reason, this work proposes the automation of the detection of the proper use of the mask at the entrance to the work areas, also providing a follow-up panel of the recorded incidents. The effectiveness of the proposal was evaluated through the detection and categorization of a data set of more than 3000 images, resulting in an accuracy of 98.6%.