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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.v2i2.36</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Internet of things, Smart parking, Real-time monitoring, Urban mobility, Parking management, Sensors, Digital payment</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>A data-driven IoT framework for real-time and predictive smart parking management in urban cities</article-title><subtitle>A data-driven IoT framework for real-time and predictive smart parking management in urban cities</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname>Saberi Najafi</surname>
		<given-names>Hashem</given-names>
	</name>
	<aff>Department of Applied Mathematics and Computer Science, Faculty of Applied Mathematics, University of Guilan, Guilan, Iran.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Fischer</surname>
		<given-names>Szabolcs</given-names>
	</name>
	<aff>Department of Highway and Railway Engineering, Széchenyi István University, Győr, Hungary.</aff>
	</contrib><contrib contrib-type="author">
	<name name-style="western">
	<surname>Esdauletova</surname>
		<given-names>Isametova Madina</given-names>
	</name>
	<aff>Isametova Madina Esdauletova, Satbayev University, Almaty, Kazakhstan.</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>20</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>A data-driven IoT framework for real-time and predictive smart parking management in urban cities</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			Urbanization and increasing vehicles have led to parking challenges, causing traffic congestion, pollution, and wasted time searching for parking spots. Traditional parking systems are inefficient due to the lack of real-time data. This project presents an IoT-based smart parking system that monitors and manages parking spaces in real time, optimizing space utilization and improving user convenience. The system uses IoT sensors to detect space occupancy and transmit the data to a central server. Users can access this information via a mobile app that displays available parking spots in real time. The system also includes automated entry and exit as well as digital payment options, reducing the need for manual intervention and streamlining the process. In tests, the system improved parking efficiency by 30%, reducing the time spent finding parking spots. Additionally, vehicle idling was minimized, leading to a 20% reduction in carbon emissions in congested areas. This IoT-based smart parking system provides a scalable solution to enhance urban mobility, offering a more sustainable and efficient approach to managing city parking.
		</p>
		</abstract>
    </article-meta>
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