Hand-Wash Sanitization Compliance Monitoring CNN Model To Maintain The Hygiene

In today’s world, with the rise of infectious diseases, proper hand-washing has become essential, particularly in hospitals and breeding grounds for pathogens. However, even in these places, pseudo dirty hand spots remain, which may be a significant vector for nosocomial diseases if proper and effective hand washing does not occur. That is why hand-washing in hospitals needs to be automated to detect hygiene without facing the problem due to skin color and brightness. While most methods deal with hand-wash compliance using video processing or sensors, we propose a Hygiene Maintenance CNN (HMCNN) Model for detecting hand-washing compliance by breaking the video into frames and utilizing transfer learning. The HMCNN model is used to get better results with 93.38% accuracy against tested consistent data than the pre-existing model. The proposed model can check the WHO guidelines for hand-washing and notify the user if it is not done correctly, helping set up a medical sector hand-wash sanitizing monitoring system.