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Data used in paper "A comparative study of calibration methods for low-cost ozone sensors in IoT platforms"

Pau Ferrer-Cid; Jose M. Barcelo-Ordinas; Jorge Garcia-Vidal; Ana Ripoll; Mar Viana


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  <identifier identifierType="DOI">10.5281/zenodo.3233516</identifier>
  <creators>
    <creator>
      <creatorName>Pau Ferrer-Cid</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2112-8516</nameIdentifier>
      <affiliation>UPC</affiliation>
    </creator>
    <creator>
      <creatorName>Jose M. Barcelo-Ordinas</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-9738-2425</nameIdentifier>
      <affiliation>UPC</affiliation>
    </creator>
    <creator>
      <creatorName>Jorge Garcia-Vidal</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0001-5969-1182</nameIdentifier>
      <affiliation>UPC</affiliation>
    </creator>
    <creator>
      <creatorName>Ana Ripoll</creatorName>
      <affiliation>CSIC</affiliation>
    </creator>
    <creator>
      <creatorName>Mar Viana</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4073-3802</nameIdentifier>
      <affiliation>CSIC</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Data used in paper "A comparative study of calibration methods for low-cost ozone sensors in IoT platforms"</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>air quality</subject>
    <subject>sensors</subject>
    <subject>low-cost</subject>
    <subject>ozone</subject>
    <subject>nitrogen dioxide</subject>
    <subject>metal-oxide</subject>
    <subject>electro-chemical</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-05-28</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3233516</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3233515</relatedIdentifier>
  </relatedIdentifiers>
  <version>v1</version>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Data used in paper &amp;quot;A comparative study of calibration methods for low-cost ozone sensors in IoT platforms&amp;quot;, submitted for publication. The data consists of: (i) raw data from three nodes with four MICS 2614 metal-oxide ozone sensors deployed in Spain, summer 2017, and (ii) raw data of five alphasense OX-B431 and NO2-B43F electro-chemical sensors, four deployed in Italy and one in Austria, summers 2017 and 2018. Moreover, we have added the calibrated data using four machine learning methods: Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR).&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/688110/">688110</awardNumber>
      <awardTitle>Collective Awareness Platform for Tropospheric Ozone Pollution</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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