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A Convolutional Neural Network-enabled IoT framework to verify COVID-19 hygiene conditions and authorize access to facilities

Pires, I.M.P. ; Capris, T. ; Takagi, Y. ; Figueiredo, D. ; Henriques, J.

Procedia Computer Science Vol. 203, Nº 0, pp. 727 - 732, August, 2022.

ISSN (print): 0000-2010
ISSN (online): 1877-0509

Scimago Journal Ranking: (in )

Digital Object Identifier: 10.1016/j.procs.2022.07.108

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COVID-19 has infected several million of individuals while claiming numerous lives. This fact raised the need to apply the measure to prevent its transmission. The use of disinfection products, wearing masks, and avoiding touching doors are important measures to avoid its spread. Thus, this work proposes a framework supported by a Convolutional Neural Network (CNN) model checking the hygienic conditions of the individuals requiring authorization to access facilities. The experimental work takes IoT devices with sensors to check: whether the users have disinfection product in their hands and a trained model to check whether individuals are also wearing masks. The achieved results highlighted the effectiveness of the proposed framework.