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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>
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    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.22105/scfa.v2i1.41</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Real-time data, Resource optimization, Sustainable cities, Smart grids, Digital transformation, Urban resilience, Automated systems.</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>AI and IoT Solutions for Efficient Public Service Delivery in Smart Cities</article-title><subtitle>AI and IoT Solutions for Efficient Public Service Delivery in Smart Cities</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Bhaduri</surname>
		<given-names>Moitreyee </given-names>
	</name>
	<aff>School of Computer Science Engineering, KIIT University, Bhubaneswar, India.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>02</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>02</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>AI and IoT Solutions for Efficient Public Service Delivery in Smart Cities</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			The objective of creating smarter cities for improved urban living involves utilizing technology to enhance public services; however, efficiently delivering these services presents a challenge. In practical terms, Artificial Intelligence (AI) and Internet of Things (IoT) offer innovative solutions such as real-time data analysis, resource optimization, and predictive capabilities to elevate the quality and responsiveness of public services. This paper examines the role of AI and IoT in key areas: traffic management, waste collection, energy distribution, and public safety within urban infrastructures. AI-powered algorithms, combined with IoT-enabled devices, facilitate the adaptive management of traffic systems based on congestion patterns. Concurrently, sensors in smart waste bins optimize collection schedules and reduce fuel expenditures. AI enhances energy management by analyzing data from IoT-connected systems to improve consumption, lower environmental impacts, and reduce costs. Moreover, AI strengthens public safety through real-time surveillance systems that identify anomalies, thereby notifying authorities of possible threats. Case studies have shown significant improvements in service efficiency, resulting in reduced traffic congestion, lower energy usage, minimized waste collection costs, and quicker emergency response times. The findings illustrate the capability of AI and IoT to streamline service provision and create sustainable, resilient urban environments. The integration of AI and IoT in smart city development has proven to be crucial for the future, offering a scalable and flexible framework to meet the evolving needs of urban populations.
		</p>
		</abstract>
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