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A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI
The world continues to witness several waves of COVID-19 spread due to the emergence of new variants of the SARS-CoV-2 virus. Stopping the spread requires synergistic efforts that include the use of technologies such as unmanned aerial vehicles and machine learning. This paper presents a novel syste...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181369/ https://www.ncbi.nlm.nih.gov/pubmed/35702485 http://dx.doi.org/10.1016/j.rsase.2022.100787 |
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author | Al Maashri, Ahmed Saleem, Ashraf Bourdoucen, Hadj Eldirdiry, Omer Al Ghadani, Ahmed |
author_facet | Al Maashri, Ahmed Saleem, Ashraf Bourdoucen, Hadj Eldirdiry, Omer Al Ghadani, Ahmed |
author_sort | Al Maashri, Ahmed |
collection | PubMed |
description | The world continues to witness several waves of COVID-19 spread due to the emergence of new variants of the SARS-CoV-2 virus. Stopping the spread requires synergistic efforts that include the use of technologies such as unmanned aerial vehicles and machine learning. This paper presents a novel system for detecting disease symptoms from a distance using unmanned aerial vehicles equipped with thermal and visual image sensors. A hardware/software system that uses thermography to accurately calculate the skin temperature of targeted individuals using thermal cameras is developed. In addition, machine vision algorithms are developed to recognize human actions such as coughing and sneezing, which are paramount symptoms of respiratory infections. The proposed system is implemented and tested in outdoor environments. The results of experiments showed that the system can determine the skin temperature of multiple targeted individuals simultaneously with an error of less than 1 °C. The field experiments showed that the developed system is capable of simultaneously measuring the temperature of more than 10 individuals in less than 5 seconds. Just to give a perspective, it takes at least 3 seconds to measure one individual's temperature if this was done using traditional methods. Furthermore, the results showed that the system has accurately detected actions such as coughing and sneezing with almost 96% accuracy at a real-time performance of 28 frames/second. |
format | Online Article Text |
id | pubmed-9181369 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91813692022-06-10 A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI Al Maashri, Ahmed Saleem, Ashraf Bourdoucen, Hadj Eldirdiry, Omer Al Ghadani, Ahmed Remote Sens Appl Article The world continues to witness several waves of COVID-19 spread due to the emergence of new variants of the SARS-CoV-2 virus. Stopping the spread requires synergistic efforts that include the use of technologies such as unmanned aerial vehicles and machine learning. This paper presents a novel system for detecting disease symptoms from a distance using unmanned aerial vehicles equipped with thermal and visual image sensors. A hardware/software system that uses thermography to accurately calculate the skin temperature of targeted individuals using thermal cameras is developed. In addition, machine vision algorithms are developed to recognize human actions such as coughing and sneezing, which are paramount symptoms of respiratory infections. The proposed system is implemented and tested in outdoor environments. The results of experiments showed that the system can determine the skin temperature of multiple targeted individuals simultaneously with an error of less than 1 °C. The field experiments showed that the developed system is capable of simultaneously measuring the temperature of more than 10 individuals in less than 5 seconds. Just to give a perspective, it takes at least 3 seconds to measure one individual's temperature if this was done using traditional methods. Furthermore, the results showed that the system has accurately detected actions such as coughing and sneezing with almost 96% accuracy at a real-time performance of 28 frames/second. Elsevier B.V. 2022-08 2022-06-09 /pmc/articles/PMC9181369/ /pubmed/35702485 http://dx.doi.org/10.1016/j.rsase.2022.100787 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Al Maashri, Ahmed Saleem, Ashraf Bourdoucen, Hadj Eldirdiry, Omer Al Ghadani, Ahmed A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title | A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title_full | A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title_fullStr | A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title_full_unstemmed | A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title_short | A novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and AI |
title_sort | novel drone-based system for accurate human temperature measurement and disease symptoms detection using thermography and ai |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181369/ https://www.ncbi.nlm.nih.gov/pubmed/35702485 http://dx.doi.org/10.1016/j.rsase.2022.100787 |
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