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                <text>Book Chapter</text>
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    <name>Book Chapter</name>
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              <text>Bibliometric Analysis of AI Research in Sustainable Smart Cities</text>
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              <text>Smart cities have the potential to improve city-wide governance, environmental sustainability, sustainable transportation, and economic growth. Urban areas may find these advantages useful in their pursuit of SDG-11 objectives. A key component of smart city architecture is the addition of artificial intelligence (AI) and other smart technology into urban areas. The Artificial Neural Network (ANN) is a major machine learning approach. A number of review studies have already been published, reflecting the substantial interest in artificial neural networks (ANN) for smart city applications. In the past, researchers have shown an interest in studying structural monitoring applications, transportation systems, cybersecurity, and the Internet of Things (IoT). But knowledge about how ANN can help Smart Cities achieve SDG-11 is limited. This paper provides a systematic bibliometric analysis of present research trends on artificial neural networks for smart cities, with an emphasis on SDG-11. The research employed a keyword-based search to obtain 131 papers for content analysis and 743 papers for descriptive analysis. Both the amount of interest in the topic and the tendency for related topics to cluster have increased exponentially, according to the findings. Urbanization, Transportation, and Eco-friendly were identified as the main topics of this study. Specifically, this evaluation focuses on particular SDG-11 issues and provides insights on research trends and thematic importance.  2025 Saravanan Krishnan, A. Jose Anand and Raghvendra Kumar.</text>
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          <name>Creator</name>
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              <text>Ravisankar A.; Ibraheem I.K.; Raha S.; Sakthi T.; Ashok J.; Tonk A.</text>
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              <text>Sustainable Development Goals: Technologies and Opportunities, pp. 189-208.</text>
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              <text>CRC Press</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1201/9781003468257-11" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003468257-11&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208311893&amp;amp;doi=10.1201%2F9781003468257-11&amp;amp;partnerID=40&amp;amp;md5=6272644db4555ba6b567ee98173d98e1" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208311893&amp;amp;doi=10.1201%2f9781003468257-11&amp;amp;partnerID=40&amp;amp;md5=6272644db4555ba6b567ee98173d98e1&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-104022798-5; 978-103273306-7</text>
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              <text>Online</text>
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              <text>Ravisankar A., Department of Management Studies, Erode Sengunthar Engineering College, Autonomous, Tamil Nadu, Erode, 638057, India; Ibraheem I.K., Department of Electronics and Communication Engineering, Uruk University, Baghdad, 10001, Iraq; Raha S., Department of Geography, Bhairab Ganguly College, Belgharia, 700056, India; Sakthi T., Department of Mechanical Engineering, National Engineering College, Kovilpatti, 628503, India; Ashok J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Tonk A., Department of Multidisciplinary Engineering, The NorthCap University, Gurugram, 122017, India</text>
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