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BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles
Catastrophic gas leak events require human First Responder Teams (FRTs) to map hazardous areas (red zones). The initial task of FRT in such events is to assess the risk according to the pollution level and to quickly evacuate civilians to prevent casualties. These teams risk their lives by manually...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320081/ https://www.ncbi.nlm.nih.gov/pubmed/35891133 http://dx.doi.org/10.3390/s22145460 |
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author | Elmakis, Oren Shaked, Tom Fishbain, Barak Degani, Amir |
author_facet | Elmakis, Oren Shaked, Tom Fishbain, Barak Degani, Amir |
author_sort | Elmakis, Oren |
collection | PubMed |
description | Catastrophic gas leak events require human First Responder Teams (FRTs) to map hazardous areas (red zones). The initial task of FRT in such events is to assess the risk according to the pollution level and to quickly evacuate civilians to prevent casualties. These teams risk their lives by manually mapping the gas dispersion. This process is currently performed using hand-held gas detectors and requires dense and exhaustive monitoring to achieve reliable maps. However, the conventional mapping process is impaired due to limited human mobility and monitoring capacities. In this context, this paper presents a method for gas sensing using unmanned aerial vehicles. The research focuses on developing a custom path planner—Boundary Red Emission Zone Estimation (BREEZE). BREEZE is an estimation approach that allows efficient red zone delineation by following its boundary. The presented approach improves the gas dispersion mapping process by performing adaptive path planning, monitoring gas dispersion in real time, and analyzing the measurements online. This approach was examined by simulating a cluttered urban site in different environmental conditions. The simulation results show the ability to autonomously perform red zone estimation faster than methods that rely on predetermined paths and with a precision higher than ninety percent. |
format | Online Article Text |
id | pubmed-9320081 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93200812022-07-27 BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles Elmakis, Oren Shaked, Tom Fishbain, Barak Degani, Amir Sensors (Basel) Article Catastrophic gas leak events require human First Responder Teams (FRTs) to map hazardous areas (red zones). The initial task of FRT in such events is to assess the risk according to the pollution level and to quickly evacuate civilians to prevent casualties. These teams risk their lives by manually mapping the gas dispersion. This process is currently performed using hand-held gas detectors and requires dense and exhaustive monitoring to achieve reliable maps. However, the conventional mapping process is impaired due to limited human mobility and monitoring capacities. In this context, this paper presents a method for gas sensing using unmanned aerial vehicles. The research focuses on developing a custom path planner—Boundary Red Emission Zone Estimation (BREEZE). BREEZE is an estimation approach that allows efficient red zone delineation by following its boundary. The presented approach improves the gas dispersion mapping process by performing adaptive path planning, monitoring gas dispersion in real time, and analyzing the measurements online. This approach was examined by simulating a cluttered urban site in different environmental conditions. The simulation results show the ability to autonomously perform red zone estimation faster than methods that rely on predetermined paths and with a precision higher than ninety percent. MDPI 2022-07-21 /pmc/articles/PMC9320081/ /pubmed/35891133 http://dx.doi.org/10.3390/s22145460 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Elmakis, Oren Shaked, Tom Fishbain, Barak Degani, Amir BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title | BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title_full | BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title_fullStr | BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title_full_unstemmed | BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title_short | BREEZE—Boundary Red Emission Zone Estimation Using Unmanned Aerial Vehicles |
title_sort | breeze—boundary red emission zone estimation using unmanned aerial vehicles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320081/ https://www.ncbi.nlm.nih.gov/pubmed/35891133 http://dx.doi.org/10.3390/s22145460 |
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