ArticleProcedia computer science2022
A Convolutional Neural Network-enabled IoT framework to verify COVID-19 hygiene conditions and authorize access to facilities.
Article in Procedia computer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A Large-Scale IoT-Based Scheme for Real-Time Prediction of Infectious Disease Symptoms.Mobile networks and applications : MONET · 2023Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
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.
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Registered trials
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