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    <journal-meta>
      <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">3042-1349</issn><issn pub-type="epub">3042-1349</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi"> https://doi.org/10.22105/sci.v2i2.37</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Cloud computing, Internet of things, Real-time analysis, Urban mobility, Machine learning</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Elastic cloud–IoT architecture for smart city traffic management: Performance, energy efficiency, and real-time analytics</article-title><subtitle>Elastic cloud–IoT architecture for smart city traffic management: Performance, energy efficiency, and real-time analytics</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Karimi</surname>
		<given-names>Habibeh</given-names>
	</name>
	<aff>Department of research center, Shiroud Municipality, Mazandaran, Iran.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Goudarzi Karim</surname>
		<given-names>Ramin</given-names>
	</name>
	<aff>Department of CIS, Stillman College, Tuscaloosa, Alabama, USA.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>25</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <volume>2</volume>
      <issue>2</issue>
      <permissions>
        <copyright-statement>© 2025 REA Press</copyright-statement>
        <copyright-year>2025</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>Elastic cloud–IoT architecture for smart city traffic management: Performance, energy efficiency, and real-time analytics</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Rapid urbanization and increasing vehicle population have led to severe traffic congestion and pollution in modern cities. Smart city initiatives leverage Internet of Things (IoT) technology to address these challenges and optimize traffic management systems. This paper explores the role of cloud computing in enhancing IoT-based traffic management by providing scalable data processing, real-time analytics, and intelligent decision-making capabilities. Cloud platforms enable seamless integration of distributed IoT devices, such as sensors and cameras, that collect traffic data. Using cloud-based machine-learning models, this system can predict traffic patterns, manage congestion, and improve road safety. The paper also discusses the benefits, challenges, and potential solutions for implementing cloud-enabled traffic management in smart cities, emphasizing improved efficiency, reduced costs, and enhanced sustainability.
		</p>
		</abstract>
    </article-meta>
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