April 30, 2020 Journal article Open Access

Boby Siswanto; Johan M. Kerta; Ranny; Devwanto D. Nugroho

DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5565750</identifier>
  <creators>
    <creator>
      <creatorName>Boby Siswanto</creatorName>
      <affiliation>Informatics, Bina Nusantara University, Bandung,  Indonesia.</affiliation>
    </creator>
    <creator>
      <creatorName>Johan M. Kerta</creatorName>
      <affiliation>Informatics, Bina Nusantara University, Bandung,  Indonesia.</affiliation>
    </creator>
    <creator>
      <creatorName>Ranny</creatorName>
      <affiliation>Informatics, Bina Nusantara University, Bandung,  Indonesia.</affiliation>
    </creator>
    <creator>
      <creatorName>Devwanto D. Nugroho</creatorName>
      <affiliation>Informatics, Bina Nusantara University, Bandung,  Indonesia.</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Automatic Detection of Carbon Dioxide  Concentration using IoT</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Carbon dioxide measurement, Internet of Things, Automatic Comparison, Classroom.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">D6653049420/2020©BEIESP</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication (BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-04-30</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5565750</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="Text">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.D6653.049420</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://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;Inside a classroom inhabited by students, carbon dioxide (CO2 ) will be produced. Number of students and inhabiting time will affect the carbon dioxide concentration. This research implementing Internet of Things (IoT) devices to measure carbon dioxide level inside a classroom. Measurements taken are comparing carbon dioxide level of student activity between exam class and regular learning class. On 100 minutes of measurement found that carbon dioxide concentration inside exam class 5% higher than carbon dioxide concentration inside regular learning class with the same number of inhabitants.&lt;/p&gt;</description>
  </descriptions>
</resource>