Automation is taking over several fields ranging from home appliance automation to autonomous vehicles to industrial plant automation and various others, and also has a major impact in facilitating new cutting-edge technologies and innovations. Thelnternet of Things, image processing and machine learning are evolving day by day. Many systems have completely changed due to this evolvement to achieve more accurate results. The attendance recording system is a typical example of this transition, starting from the traditional signature-based on-paper methods to fingerprint-based systems to face recognition-based systems. The major drawback of different algorithms for face recognition-based attendance system is that one person can scan his/her face by facing the camera and once the face is recognized, his/her attendance will be marked whether or not the person attends the lecture after that. In this paper, we have proposed an efficient algorithm to eliminate such proxy attendances. Furthermore, we have added IoT capabilities to our system in order to increase the ease of access to the collected attendance and to maintain transparency.
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