This document describes a face mask detection system using artificial intelligence. The system is designed as a two-phase model, with the first phase involving training a convolutional neural network (CNN) model on a dataset of images containing faces with and without masks. In the second phase, the trained model can detect masks in real-time videos and classify faces as with or without a mask. The goal is to implement the system in public places to help enforce mask policies and reduce COVID-19 transmission. The model achieves accurate detection on both static images and videos by using data augmentation techniques to increase variability in the training dataset.