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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">3042-0180</issn><issn pub-type="epub">3042-0180</issn><publisher>
      	<publisher-name>REA Press</publisher-name>
      </publisher>
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    <article-meta>
      <article-id pub-id-type="doi"> https://doi.org/10.22105/scfa.v2i1.43 </article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Smart grid, Internet of things, Artificial intelligence, Urban optimization, Energy efficiency.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>IoT and AI for Smart Grid Optimization in Urban Areas</article-title><subtitle>IoT and AI for Smart Grid Optimization in Urban Areas</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Pal</surname>
		<given-names>Gourab </given-names>
	</name>
	<aff>School of Computer Engineering, KIIT (Deemed to be) University, Bhubaneswar, Odisha, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>03</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>24</day>
        <month>03</month>
        <year>2025</year>
      </pub-date>
      <volume>2</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>IoT and AI for Smart Grid Optimization in Urban Areas</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			As cities grow and the need for energy rises, optimizing power distribution and enhancing grid efficiency becomes vital. This study explores how the integration of the Internet of Things (IoT) and Artificial Intelligence (AI) can be utilized to improve smart grid systems in urban areas. This strategy aims to enhance energy distribution, cut down on inefficiencies, and lessen power outages by using IoT devices for immediate data gathering and AI-powered predictive algorithms for informed decision-making. Additionally, the system's capability to identify irregularities and forecast equipment failures aids in lowering maintenance expenses. Simulation results from a model urban grid indicate that smart grid solutions driven by AI and IoT can result in superior energy management, greater grid reliability, and promote more sustainable development in urban settings.
		</p>
		</abstract>
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