Abstract
COVID-19 pandemic has impacted the lives of individuals, organizations, markets, and the whole world in a way that has changed the functioning of all the systems. To get going, some try to adapt to working online, children started studying online and people started ordering food online. While this is still going on, there are many people whose jobs demand physical presence at workplaces and they have no choice but to be exposed to the virus while keeping our society functioning. People are needed to adapt to the new “normal” by practicing social distancing and wearing masks. Wearing masks is the most effective means of prevention of Covid-19. To ensure this, we built a web application that aims at keeping people advised to wear masks constantly with the help of an integrated facemask detection and face-recognition system. The proposed system initially detects whether the person in the real-time video feed is wearing a mask or not and then recognizes the face of the person if they are not wearing a mask. Finally, the proposed system alerts that specific violator to wear a mask through an auto-generated email to his personal email id. The application also allows the admin and the violators to log in and access the list of fines levied along with photo evidence.
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Bhargav, G.P., Reddy, K.S., Viswanath, A., Teja, B., Byju, A.P. (2022). An Integrated Facemask Detection with Face Recognition and Alert System Using MobileNetV2. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 286. Springer, Singapore. https://doi.org/10.1007/978-981-16-9873-6_7
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DOI: https://doi.org/10.1007/978-981-16-9873-6_7
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