An IoT Application Framework Using Deep Learning for Face Mask Detection

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Pravat Kumar Routray, Binod Kumar Pattanayak, Mihir Narayan Mohanty


A facemask covering nose and mouth is one of the most effective ways to protect against infection and to spread the coronavirus. This safeguard rule is applied by almost all governments. For automation, we have developed an approach based on deep learning to detect the mask. The approach has been extended to an Internet of Things (IoT) based framework that can be an element of a smart city to keep people safe. Since health safety is a major challenge, this paper proposes an automatic detection process. A convolutional neural network with transfer learning is used for the detection. This model is included in an IoT architecture for automation. The results of testing the approach are excellent in terms of accuracy. In addition, the module for IoT works well, as verified in the study, and also appearsĀ  to be useful for the Internet of Medical Things.

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