IoT-Deep Learning Based Face Mask Detection System for Entrance and Exit Door

During the pandemic, it has been seen that global population follows guidelines issued by health organization regarding wearing face masks, but some people do not take care of this and use masks. The objective proposed system, Wollega University Face Mask Detection System (WUFMDS), is to restrict who are a mask on door side identifying from or open if incoming person mask. This system based Internet Things (IoT) Deep Learning algorithm called Convolutional Neural Network (CNN). For purpose, images with without masks were collected as samples university. CNN used detect classify IoT module controls operation classification response sent algorithm. was tested lively dummy in order ensure functionality detection developed software applications for model working defined objectives. Our had 99.36% accuracy training dataset 99.29% validation set. Hence, could be automatic identification operate allow pass through while keeping closed when no found face.