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      <journal-id journal-id-type="nlm-ta">REA Press</journal-id>
      <journal-id journal-id-type="publisher-id">Null</journal-id>
      <journal-title>REA Press</journal-title><issn pub-type="ppub">3042-0180</issn><issn pub-type="epub">3042-0180</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/scfa.v1i3.47</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Predictive analytics, Resource optimization, Cloud computing, Environmental monitoring.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>IoT-Driven Water Quality Monitoring Systems for Smart Cities</article-title><subtitle>IoT-Driven Water Quality Monitoring Systems for Smart Cities</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Behera</surname>
		<given-names>Suvam</given-names>
	</name>
	<aff>School of Computer Science Engineering, KIIT University, Bhubaneswar, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>08</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>23</day>
        <month>08</month>
        <year>2024</year>
      </pub-date>
      <volume>1</volume>
      <issue>3</issue>
      <permissions>
        <copyright-statement>© 2024 REA Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>IoT-Driven Water Quality Monitoring Systems for Smart Cities</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Water quality monitoring systems in smart cities, driven by the Internet of Things (IoT), utilize interconnected sensors to continuously measure parameters such as pH, turbidity, and contaminants. These systems offer real-time data and analysis, making it possible to quickly identify problems like contamination or leaks. By incorporating machine learning, they aid in forecasting trends and enhancing resource management. The architecture of the system consists of sensing, communication, and data processing layers, with wireless protocols used to transmit information for analysis. These systems enhance urban water management, promote sustainable development, and efficiently address water quality challenges.	
		</p>
		</abstract>
    </article-meta>
  </front>
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