Work

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

Year: 2022

Type: conference-paper

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.

Source: Procedia Computer Science

DOI: 10.1016/j.procs.2022.07.108

Authors: Ticiana Capris, Yuka Takagi, Diana Figueiredo, João Henriques, Ivan Miguel Pires

Institutions: Universidade Politécnica de Viseu, University of Coimbra, University of Trás-os-Montes and Alto Douro, University of Beira Interior

Language: English

Topic: Internet of Things and AI

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond