A Real time analysis of Face Mask: Safest Side from COVID-19

Abstract

In the present scenario of COVID -19 pandemic to detect the face mask is an important application of machine learning and Internet of Things and having highly significant for the same. In the recent time significance of machine learning project growing very fast day by day. In the proposed work, we will introduce the innovative face mask detection methods by using the visual features of face like facial tone, facial expression rather than conventional old face mask detection methods which was only based to detect eyes states and the position of eyes to identify the relative position of mask. face mask detection is very challenging task because it involves the many complex aspects like intensity variation due to the effect of lighting, person wears spaces and glasses or having beard on face or some dark makeup on face. In this work we propose to implement an IoT based hardware system based on infrared light sensor to overcome the challenges face during mask detection. In the proposed work, we have followed the face detection step, the facial component analysis and identify the features which is effective and important for face mask detection than we have to extract and track the features in the sequence of video frames. Proposed system has been tested and implemented in a real environment and the system generate the accuracy of 100%.