<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" "journalpublishing.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article">
  <front>
    <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.v2i3.46</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Internet of things, Smart grid, Urban energy management, Demand response, Advanced metering infrastructure</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>An AI–IoT integrated smart grid model for resilient and sustainable urban energy management</article-title><subtitle>An AI–IoT integrated smart grid model for resilient and sustainable urban energy management</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Wang</surname>
		<given-names>Mingyue</given-names>
	</name>
	<aff>School of computer and information, Lanzhou University of Technology, China.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Dimov</surname>
		<given-names>Aleksandar</given-names>
	</name>
	<aff>Faculty of Mathematics and Informatics (FMI), Sofia University, Bulgaria.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>09</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>26</day>
        <month>09</month>
        <year>2025</year>
      </pub-date>
      <volume>2</volume>
      <issue>3</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>An AI–IoT integrated smart grid model for resilient and sustainable urban energy management</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			As urban populations grow, cities face increasing pressure to manage energy consumption efficiently. The advent of IoT-based smart grid technologies provides a promising solution, enabling real-time monitoring, data analysis, and predictive maintenance to optimize energy use. This paper investigates various IoT applications in smart grids, focusing on their role in urban energy management. It examines Advanced Metering Infrastructure (AMI), Demand Response (DR), and Distributed Energy Resource (DER) integration. Through a comparative analysis of current strategies, the study highlights the strengths and challenges of IoT-based smart grids in urban areas and proposes future improvements for scalability and security. This research aims to advance smart grid capabilities to meet the dynamic energy demands of urban environments.
		</p>
		</abstract>
    </article-meta>
  </front>
  <body></body>
  <back>
    <ack>
      <p>null</p>
    </ack>
  </back>
</article>