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Face Mask Detection Alert System

Maahi Khemchandani, Rohit Satish Jawale, Nilesh Prakash Aawale, Kaif Naushad Khan

Abstract


The COVID-19 coronavirus epidemic is widely spreading around the world, which is why wearing face masks in public is becoming more popular. Since the WHO has made wearing masks mandatory to prevent this deadly virus, wearing face masks regularly is an essential measure until the virus is completely eradicated. Several preventive measures are being considered to decrease the spread of disease and one of them is wearing masks in crowded areas. To solve the problem, an efficient approach of using a Convolution Neural Network (CNN) deep learning algorithm that allows detecting a person in real-time if the person is wearing a mask or not using a CCTV camera, using datasets consisting of individuals covering and not covering their faces with masks that used to train our model, after that, a person is denied access to places where authorities have strictly asked to wear a face mask. After denying access to the person, authorities will get an alert email in real-time, and the person is instructed to pop up a Warning Message where a person would be advised to wear a mask before getting access. The accuracy of our model is 95.05% during training and validation.


Keywords


Covid19, alert system, CNN, facemask, datasets

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References


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