Face Mask Detection with Body Temperature Monitoring Using IoT

Recent years have seen a rise in the prevalence of the large family of viruses known as coronavirus common, communicable, and harmful to all human beings. It travels from person to person by exhaling the infectious breath, which leaves virus droplets on various surfaces, which are subsequently inhaled by other people, who then contract the infection. Therefore, it has become crucial that we safeguard both ourselves and those who are close to us from this circumstance. We may take safeguards like maintaining social distance, washing our hands every two hours, using hand sanitizer, and most importantly wearing a mask. For offices or any other setting where there are lots of people working, this paper suggests a method to determine if a face mask is used or not. For face mask detection used Convolutional neural network model used here is the MobileNetV2 architecture. MobileNetV2 model is a network model using depth wise separable convolution as its basic unit the model is evaluated with live video streaming with good accuracy after being trained on a real-world dataset.