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Coupling multifunction drones with AI in the fight against the coronavirus pandemic
When COVID-19 was declared as a pandemic by the World Health Organization on 11 March 2020, national governments and health authorities across the world begun considering different preventive measures to fight against the coronavirus outbreak. Researchers and tech companies worldwide have been striv...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577400/ http://dx.doi.org/10.1007/s00607-021-01022-9 |
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author | Almalki, Faris A. Alotaibi, Abdullah A. Angelides, Marios C. |
author_facet | Almalki, Faris A. Alotaibi, Abdullah A. Angelides, Marios C. |
author_sort | Almalki, Faris A. |
collection | PubMed |
description | When COVID-19 was declared as a pandemic by the World Health Organization on 11 March 2020, national governments and health authorities across the world begun considering different preventive measures to fight against the coronavirus outbreak. Researchers and tech companies worldwide have been striving to utilize advanced technologies to aid in the fight against the Covid-19 outbreak. This paper aims to couple multifunction drone with AI to deliver wireless services that will help the fight against the Coronavirus pandemic. The proposed drone-eye-system with its thermal imaging cameras and an AI framework utilizes a Convolutional Neural Network (CNN) with its Modified Artificial Neural Network (MANN) for face mask detection of people wearing masks in public. The system can perform basic diagnostic functions such as elevated body temperatures for helping minimize the risk of spreading the infection through close contact. The AI framework evolve an optimized elevation angle [Formula: see text] and altitude [Formula: see text] to enhance wireless connectivity between a drone and a ground station, which in turn leads to better throughput and power consumption. The proposed framework has been developed using the MATLAB toolbox and shows promising results with an accuracy of face mask detection of 82.63%, with an F1-score of 0.98, and an enhanced by 10% link budget parameters. |
format | Online Article Text |
id | pubmed-8577400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-85774002021-11-10 Coupling multifunction drones with AI in the fight against the coronavirus pandemic Almalki, Faris A. Alotaibi, Abdullah A. Angelides, Marios C. Computing Regular Paper When COVID-19 was declared as a pandemic by the World Health Organization on 11 March 2020, national governments and health authorities across the world begun considering different preventive measures to fight against the coronavirus outbreak. Researchers and tech companies worldwide have been striving to utilize advanced technologies to aid in the fight against the Covid-19 outbreak. This paper aims to couple multifunction drone with AI to deliver wireless services that will help the fight against the Coronavirus pandemic. The proposed drone-eye-system with its thermal imaging cameras and an AI framework utilizes a Convolutional Neural Network (CNN) with its Modified Artificial Neural Network (MANN) for face mask detection of people wearing masks in public. The system can perform basic diagnostic functions such as elevated body temperatures for helping minimize the risk of spreading the infection through close contact. The AI framework evolve an optimized elevation angle [Formula: see text] and altitude [Formula: see text] to enhance wireless connectivity between a drone and a ground station, which in turn leads to better throughput and power consumption. The proposed framework has been developed using the MATLAB toolbox and shows promising results with an accuracy of face mask detection of 82.63%, with an F1-score of 0.98, and an enhanced by 10% link budget parameters. Springer Vienna 2021-11-09 2022 /pmc/articles/PMC8577400/ http://dx.doi.org/10.1007/s00607-021-01022-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Regular Paper Almalki, Faris A. Alotaibi, Abdullah A. Angelides, Marios C. Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title | Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title_full | Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title_fullStr | Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title_full_unstemmed | Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title_short | Coupling multifunction drones with AI in the fight against the coronavirus pandemic |
title_sort | coupling multifunction drones with ai in the fight against the coronavirus pandemic |
topic | Regular Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577400/ http://dx.doi.org/10.1007/s00607-021-01022-9 |
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