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7th IEEE International conference for Convergence in Technology, I2CT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1992602

ABSTRACT

The outbreak of the COVID-19 pandemic caused by the novel coronavirus has disrupted global health systems and changed the way of life. Leveraging the potential of technology has become indispensable to ensure safety as new strains emerge. In this paper, we propose a low-cost AI-based screening system that can be installed at various locations. The objective of our solution is to automate the task of face mask detection, checking for social distancing, and body temperature scanning. The dataset used for our AI model consisted of 2314 images combining those without a mask and those with an artificial mask attached using computer vision techniques. These three functionalities were carried out by combining AI and IoT technologies. Specifically, we employed the SingleShot-Multibox detector (SSD) and ResNet-10 architecture as the first part of our model for face detection. MobileNetV2 architecture was used as the second part of the model for binary classification (with or without mask). Various IoT components were integrated to achieve a real-time screening process and subsequently simulate entry access or denial. Our proposed model outperformed other existing solutions by achieving an accuracy of 99% and an F1 score of 0.99. © 2022 IEEE.

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