| Literature DB >> 35974969 |
Ticiana Capris1, Yuka Takagi1, Diana Figueiredo1, João Henriques1,2,3, Ivan Miguel Pires4,5.
Abstract
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.Entities:
Keywords: Convolutional Neural Network; IoT, Covid-19; Sensor
Year: 2022 PMID: 35974969 PMCID: PMC9374321 DOI: 10.1016/j.procs.2022.07.108
Source DB: PubMed Journal: Procedia Comput Sci