Abstract
Tracking coronavirus patients and determining their close contacts (as part of COVID-19 mapping) have been huge challenges. In universities, in particular, there are many students and large gatherings who are at a higher risk of obtaining COVID-19. Many smart attendance management systems have been proposed that are based on RFID and fingerprint sensor modules, facial recognition, etc. However, these techniques operate with specific requirements, such as GPUs and large memories/datasets, or by combining recognizance and thermal cameras. To solve these issues and reduce costs, we designed an Internet of Things (IoT)-based intelligent attendance management system. In this paper, we compare the advantages/disadvantages of existing smart attendance management systems. We designed an IoT-based intelligent attendance management system based on the cloud, a web server, Google API, a non-contact body temperature sensor, and the Raspberry Pi 4 module (4G). We conducted a survey at a university and summarized the satisfaction levels of using our system.
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