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Chemical gas sensor array dataset

To address drift in chemical sensing, an extensive dataset was collected over a period of three years. An array of 16 metal-oxide gas sensors was exposed to six different volatile organic compounds at different concentration levels under tightly-controlled operating conditions. Moreover, the generat...

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Detalles Bibliográficos
Autores principales: Fonollosa, Jordi, Rodríguez-Luján, Irene, Huerta, Ramón
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510048/
https://www.ncbi.nlm.nih.gov/pubmed/26217723
http://dx.doi.org/10.1016/j.dib.2015.01.003
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author Fonollosa, Jordi
Rodríguez-Luján, Irene
Huerta, Ramón
author_facet Fonollosa, Jordi
Rodríguez-Luján, Irene
Huerta, Ramón
author_sort Fonollosa, Jordi
collection PubMed
description To address drift in chemical sensing, an extensive dataset was collected over a period of three years. An array of 16 metal-oxide gas sensors was exposed to six different volatile organic compounds at different concentration levels under tightly-controlled operating conditions. Moreover, the generated dataset is suitable to tackle a variety of challenges in chemical sensing such as sensor drift, sensor failure or system calibration. The data is related to “Chemical gas sensor drift compensation using classifier ensembles”, by Vergara et al. [1], and “On the calibration of sensor arrays for pattern recognition using the minimal number of experiments”, by Rodriguez-Lujan et al. [2] The dataset can be accessed publicly at the UCI repository upon citation of: http://archive.ics.uci.edu/ml/datasets/Gas+Sensor+Array+Drift+Dataset+at+Different+Concentrations
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spelling pubmed-45100482015-07-27 Chemical gas sensor array dataset Fonollosa, Jordi Rodríguez-Luján, Irene Huerta, Ramón Data Brief Data Article To address drift in chemical sensing, an extensive dataset was collected over a period of three years. An array of 16 metal-oxide gas sensors was exposed to six different volatile organic compounds at different concentration levels under tightly-controlled operating conditions. Moreover, the generated dataset is suitable to tackle a variety of challenges in chemical sensing such as sensor drift, sensor failure or system calibration. The data is related to “Chemical gas sensor drift compensation using classifier ensembles”, by Vergara et al. [1], and “On the calibration of sensor arrays for pattern recognition using the minimal number of experiments”, by Rodriguez-Lujan et al. [2] The dataset can be accessed publicly at the UCI repository upon citation of: http://archive.ics.uci.edu/ml/datasets/Gas+Sensor+Array+Drift+Dataset+at+Different+Concentrations Elsevier 2015-02-16 /pmc/articles/PMC4510048/ /pubmed/26217723 http://dx.doi.org/10.1016/j.dib.2015.01.003 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Fonollosa, Jordi
Rodríguez-Luján, Irene
Huerta, Ramón
Chemical gas sensor array dataset
title Chemical gas sensor array dataset
title_full Chemical gas sensor array dataset
title_fullStr Chemical gas sensor array dataset
title_full_unstemmed Chemical gas sensor array dataset
title_short Chemical gas sensor array dataset
title_sort chemical gas sensor array dataset
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4510048/
https://www.ncbi.nlm.nih.gov/pubmed/26217723
http://dx.doi.org/10.1016/j.dib.2015.01.003
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