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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">3009-3732</issn><issn pub-type="epub">3009-3732</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
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    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.31181/sa31202540</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>AI-driven cloud computing, Smart city analytics, Urban data management, Internet of things (IoT), Sustainable urban development.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>AI-Driven Cloud Solutions for Smart City Data Analytics</article-title><subtitle>AI-Driven Cloud Solutions for Smart City Data Analytics</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Rakshit</surname>
		<given-names>Ishita </given-names>
	</name>
	<aff>School of Computer Science Engineering, KIIT University, Bhubaneswar, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>03</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>26</day>
        <month>03</month>
        <year>2025</year>
      </pub-date>
      <volume>3</volume>
      <issue>1</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>AI-Driven Cloud Solutions for Smart City Data Analytics</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Incorporating AI-powered cloud solutions into the analytics of smart city data offers a groundbreaking method for urban management and evolution. As cities around the globe face rising populations, limited resources, and the pressing demand for sustainability, the adoption of advanced technologies becomes essential. This paper examines how cloud computing and Artificial Intelligence (AI) work together to enhance the capabilities for processing, storing, and analyzing data in smart cities. AI-based cloud solutions allow for real-time data gathering from diverse sources such as IoT devices, sensors, and social media platforms. These solutions streamline the collection and processing of large data volumes, enabling city planners and officials to generate practical insights. By utilizing machine learning techniques, cities can forecast traffic trends, optimize energy use, and enhance public safety, thus improving urban living conditions. Additionally, cloud-based systems offer the necessary scalability and flexibility to effectively manage the ever-changing nature of urban data. They promote collaborative frameworks that foster stakeholder involvement and innovation through open data initiatives and civic engagement. The availability of cloud services also levels the playing field for data utilization, equipping smaller municipalities with advanced analytical capabilities that were once exclusive to larger cities.
		</p>
		</abstract>
    </article-meta>
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