Data set from chemical sensor array exposed to turbulent gas mixtures

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dc.contributor.author Fonollosa, Jordi
dc.contributor.author Rodríguez-Luján, Irene
dc.contributor.author Trincavelli, Marco
dc.contributor.author Huerta, Ramón
dc.contributor.other UAM. Departamento de Ingeniería Informática es_ES
dc.date.accessioned 2016-10-14T15:59:27Z
dc.date.available 2016-10-14T15:59:27Z
dc.date.issued 2015-06-01
dc.identifier.citation Data in Brief 3 (2015): 216-220 en_US
dc.identifier.issn 2352-3409
dc.identifier.uri http://hdl.handle.net/10486/674188
dc.description.abstract A chemical detection platform composed of 8 chemo-resistive gas sensors was exposed to turbulent gas mixtures generated naturally in a wind tunnel. The acquired time series of the sensors are provided. The experimental setup was designed to test gas sensors in realistic environments. Traditionally, chemical detection systems based on chemo-resistive sensors include a gas chamber to control the sample air flow and minimize turbulence. Instead, we utilized a wind tunnel with two independent gas sources that generate two gas plumes. The plumes get naturally mixed along a turbulent flow and reproduce the gas concentration fluctuations observed in natural environments. Hence, the gas sensors can capture the spatio-temporal information contained in the gas plumes. The sensor array was exposed to binary mixtures of ethylene with either methane or carbon monoxide. Volatiles were released at four different rates to induce different concentration levels in the vicinity of the sensor array. Each configuration was repeated 6 times, for a total of 180 measurements. The data is related to "Chemical Discrimination in Turbulent Gas Mixtures with MOX Sensors Validated by Gas Chromatography-Mass Spectrometry", by Fonollosa et al. [1]. The dataset can be accessed publicly at the UCI repository upon citation of [1]: http://archive.ics.uci.edu/ml/datasets/Gas+senso+rarray+exposed+to+turbulent+gas+mixtures. en_US
dc.description.sponsorship This work has been supported by the California Institute for Telecommunications and Information Technology (CALIT2) under Grant Number 2014 CSRO 136. en_US
dc.format.extent 5 pag. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Elsevier Inc. en_US
dc.relation.ispartof Data in Brief en_US
dc.rights © 2015 The Authors en_US
dc.subject.other Chemical Sensing en_US
dc.subject.other Chemometrics en_US
dc.subject.other Electronic nose en_US
dc.subject.other Machine learning en_US
dc.subject.other Machine olfaction en_US
dc.title Data set from chemical sensor array exposed to turbulent gas mixtures en_US
dc.type article en_US
dc.subject.eciencia Informática es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.dib.2015.02.022
dc.identifier.doi 10.1016/j.dib.2015.02.022
dc.identifier.publicationfirstpage 216
dc.identifier.publicationlastpage 220
dc.identifier.publicationvolume 3
dc.type.version info:eu-repo/semantics/publishedVersion en
dc.contributor.group Aprendizaje Automático (ING EPS-001) es_ES
dc.rights.cc Reconocimiento es_ES
dc.rights.accessRights openAccess en
dc.authorUAM Huerta Rico, Ramón (259903)


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