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The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter

This study presents a detailed analysis of an air monitoring development system using quadcopters. The data collecting method is based on gas dispersion investigation to pinpoint the gas source location and determine the gas concentration level. Due to its flexibility and low cost, a quadcopter was...

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Autores principales: Kuantama, Endrowednes, Tarca, Radu, Dzitac, Simona, Dzitac, Ioan, Vesselenyi, Tiberiu, Tarca, Ioan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766846/
https://www.ncbi.nlm.nih.gov/pubmed/31489887
http://dx.doi.org/10.3390/s19183849
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author Kuantama, Endrowednes
Tarca, Radu
Dzitac, Simona
Dzitac, Ioan
Vesselenyi, Tiberiu
Tarca, Ioan
author_facet Kuantama, Endrowednes
Tarca, Radu
Dzitac, Simona
Dzitac, Ioan
Vesselenyi, Tiberiu
Tarca, Ioan
author_sort Kuantama, Endrowednes
collection PubMed
description This study presents a detailed analysis of an air monitoring development system using quadcopters. The data collecting method is based on gas dispersion investigation to pinpoint the gas source location and determine the gas concentration level. Due to its flexibility and low cost, a quadcopter was integrated with air monitoring sensors to collect the required data. The analysis started with the sensor placement on the quadcopter and their correlation with the generated vortex. The reliability and response time of the sensor used determine the duration of the data collection process. The dynamic nature of the environment makes the technique of air monitoring of topmost concern. The pattern method has been adapted to the data collection process in which area scanning was marked using a point of interest or grid point. The experiments were done by manipulating a carbon monoxide (CO) source, with data readings being made in two ways: point source with eight sampling points arranged in a square pattern, and non-point source with 24 sampling points in a grid pattern. The quadcopter collected data while in a hover state with 10 s sampling times at each point. The analysis of variance method (ANOVA) was also used as the statistical algorithm to analyze the vector of gas dispersion. In order to tackle the uncertainty of wind, a bivariate Gaussian kernel analysis was used to get an estimation of the gas source area. The result showed that the grid pattern measurement was useful in obtaining more accurate data of the gas source location and the gas concentration. The vortex field generated by the propeller was used to speed up the accumulation of the gas particles to the sensor. The dynamic nature of the wind caused the gas flow vector to change constantly. Thus, more sampling points were preferred, to improve the accuracy of the gas source location prediction.
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spelling pubmed-67668462019-10-02 The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter Kuantama, Endrowednes Tarca, Radu Dzitac, Simona Dzitac, Ioan Vesselenyi, Tiberiu Tarca, Ioan Sensors (Basel) Article This study presents a detailed analysis of an air monitoring development system using quadcopters. The data collecting method is based on gas dispersion investigation to pinpoint the gas source location and determine the gas concentration level. Due to its flexibility and low cost, a quadcopter was integrated with air monitoring sensors to collect the required data. The analysis started with the sensor placement on the quadcopter and their correlation with the generated vortex. The reliability and response time of the sensor used determine the duration of the data collection process. The dynamic nature of the environment makes the technique of air monitoring of topmost concern. The pattern method has been adapted to the data collection process in which area scanning was marked using a point of interest or grid point. The experiments were done by manipulating a carbon monoxide (CO) source, with data readings being made in two ways: point source with eight sampling points arranged in a square pattern, and non-point source with 24 sampling points in a grid pattern. The quadcopter collected data while in a hover state with 10 s sampling times at each point. The analysis of variance method (ANOVA) was also used as the statistical algorithm to analyze the vector of gas dispersion. In order to tackle the uncertainty of wind, a bivariate Gaussian kernel analysis was used to get an estimation of the gas source area. The result showed that the grid pattern measurement was useful in obtaining more accurate data of the gas source location and the gas concentration. The vortex field generated by the propeller was used to speed up the accumulation of the gas particles to the sensor. The dynamic nature of the wind caused the gas flow vector to change constantly. Thus, more sampling points were preferred, to improve the accuracy of the gas source location prediction. MDPI 2019-09-06 /pmc/articles/PMC6766846/ /pubmed/31489887 http://dx.doi.org/10.3390/s19183849 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kuantama, Endrowednes
Tarca, Radu
Dzitac, Simona
Dzitac, Ioan
Vesselenyi, Tiberiu
Tarca, Ioan
The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title_full The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title_fullStr The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title_full_unstemmed The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title_short The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter
title_sort design and experimental development of air scanning using a sniffer quadcopter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766846/
https://www.ncbi.nlm.nih.gov/pubmed/31489887
http://dx.doi.org/10.3390/s19183849
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