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Machine learning approach to control and monitor people to prevent COVID-19

Ever since the surge of the COVID-19 pandemic, the countries all around the globe have been struggling to stand on their feet. The government has been focusing on finding various root causes of the spread. While the government is progressing with vaccination drives, the primary preventive measures must be followed at all costs. In this paper, we propose a low-cost, scalable device that detects the presence of a face mask on human faces and temperature of the person when the camera detects somebody trying to enter. This device would ideally be placed in the entrance of public places that include hospitals, temples, offices, ATMs, malls etc. Here, the concept of transfer learning is used in neural networks to get an out put regarding the presence or absence of masks. TensorFlow tools are used for Image Augmentation. A non-contact temperature sensor is used for measuring the temperature. If the person entering is wearing mask and the temperature recorded is minimum, the door will open and the hand sanitizer will be sprayed when the device detects hands. If either of these conditions are not satisfied, the door will not open and the person will not be allowed to enter. © 2022 Author(s).