The suggested system consists of the following steps: acquiring CCTV photos, processing those images, locating faces in the images, extracting information from those images, and recognising faces. Principal component analysis (PCA) and convolutional neural network (CNN) are the two feature extraction technologies we employ. We employ K-nearest neighbour (KNN), decision trees, random forests, and CNN. Applying these algorithms to the dataset of more than 40K real-time photos recorded at various conditions, including light intensity, rotation, and scale for simulation and performance evaluation, results in the recognition. Finally, we were able to recognise faces with over 90% accuracy and a minimum amount of computation time. A face shield, an item of personal protective equipment (PPE), aims to protect the wearer's entire face (or part of it) from hazards such as flying objects and road debris, chemical splashes (in laboratories or in industry), or potentially infectious materials (in medical and laboratory environments). Depending on the type used, a face shield may protect its wearer from a physical hazard, chemical splashes, or biological hazards.