International Journal of Scientific Research and Engineering Development

The rapid spread of infectious diseases has highlighted the importance of strict safety protocols in healthcare environments, especially in Intensive Care Units (ICUs). Wearing face masks is one of the most effective preventive measures to reduce transmission. This project presents an automated Face Mask Detection System designed specifically for ICU environments using computer vision and deep learning techniques.The system utilizes image processing with the help of OpenCV for real-time face detection and a Convolutional Neural Network (CNN) model to classify whether a person is wearing a mask or not. The model is trained on a dataset containing images of masked and unmasked faces, enabling it to achieve high accuracy in diverse conditions. The system continuously monitors video input from surveillance cameras installed in the ICU and identifies individuals who are not complying with mask protocols.

Aishwarya Hosale, Vaibhavi Kore, Sakshi Ugade, Saif Naikwadi, Shubham Sonar,"Face Mask Detection For ICU" International Journal of Scientific Research and Engineering Development, V9(3): Page(83-85) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.