The spread of contagious diseases is a global problem, especially in public areas, where it is difficult to use traditional methods of monitoring. It is possible to reduce the spread of viruses, including Covid-19, by wearing a face mask, as recommended by WHO. There is a need for professional monitoring methods to effectively ensure people’s adherence to the WHO recommendation. Recently, deep learning has shown huge success in a variety of real-world applications. Computer vision, which is a branch of deep learning, could be used to develop a powerful face mask monitoring system. In this project, we present a robust deep CNN model to detect the presence of face masks among individuals as a monitoring solution. The proposed model was trained using the Roboflow platform with a new dataset created by us. The experi- mental results showed that the proposed approach outperformed the state-of-the-art techniques by obtaining a Mean Average Precision(mAP) value of 91.1