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Contactless Attendance Tracking using Face Recognition and Sensor based Techniques: A Pilot Study

Stepping out of home without mask is impossible in today’s situation due to the global pandemic. This crisis has forced the world to shut down affecting its economy, day-to-day routine, and people’s livelihood. Today, people are adapting to this new normal in a gradual manner. Therefore, making contactless attendance tracking and screening is an essential part in all the organizations. This will be solved by building a technology which will do multiple functions like detecting faces of people with their masks on and reading their body temperature involving various techniques computer vision and deep learning using Python, OpenCV, and TensorFlow/Keras and also some sensors like Infrared Temperature Sensor. The output values of these modules will be uploaded in cloud storage and can be viewed remotely. It is highly possible to reduce the spread of the virus and promote social distancing as per the government norms by using such technology driven solutions. The aim of this paper is to provide a technical review on such existing technologies and suggesting some solutions for additional features.