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Addressing Urbanism Challenges With AI and the Internet of Things

Adnène Arbi Imene Ouali Achraf Wali

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English
Engineering Science Reference
08 May 2025
Addressing the challenges of urbanism requires innovative solutions that can manage the complexities of growing cities. The integration of artificial intelligence (AI) and Internet of Things (IoT) offers powerful tools to tackle issues like traffic congestion, waste management, energy efficiency, and public safety. Through smart sensors, data analytics, and machine learning algorithms, AI and IoT can provide real-time insights and automation, enabling cities to become more adaptive, sustainable, and livable. By harnessing these technologies, urban planners can optimize resources, improve citizen services, and create safer, greener environments. As urban populations rise, further research into AI and IoT may help communities build smarter cities for the future. Addressing Urbanism Challenges With AI and the Internet of Things delves into the transformative potential of advanced technologies in addressing these complex global issues. It presents a comprehensive exploration of how cutting-edge technologies can drive positive change and foster sustainable development worldwide. This book covers topics such as data science, energy engineering, and smart technology, and is a useful resource for business owners, engineers, environmentalists, urban designers, academicians, and researchers.
Edited by:   , ,
Imprint:   Engineering Science Reference
Country of Publication:   United States
Dimensions:   Height: 254mm,  Width: 178mm, 
ISBN:   9798369381427
Pages:   338
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Adnène Arbi is an Associate Professor at the National Institute of Applied Sciences and Technology (INSAT). His current research activities are in the field of Applied Mathematics and Artificial Intelligence (AI). Major research projects include modelling of mathematical neural networks and model predictive control. He published more than 34 papers in peer-reviewed international journals since 2014. He edited two books on Neural Networks, Iot, AI, and Data-driven control published in 2025-2026. He is a member of the editorial board of the journals: Journal of Algorithms & Computational Technology, Innovative Applied Mathematics and Computational Sciences, Frontiers in Applied Mathematics and Statistics and Karshi Multidisciplinary International Scientific Journal. He served as a reviewer for more than 100 papers for international journals such as the IMA Journal of Mathematical Control and Information, Mathematics and Computers in Simulation, Chaos, Solitons & Fractals, Journal of Intelligent & Fuzzy Systems, Computational and Applied Mathematics. American Association for Sciences and Technology, Mathematical Methods in the Applied Sciences, Neural Networks, Asian Journal of Control, Neural processing letters, International Journal of Statistical Distributions and Applications, IEEE Transactions on Neural Networks and Learning Systems, IMA Journal of Mathematical Control and Information, JCAS: International Journal of Control, Automation and Systems. He is an Expert/Consultant for the Science for Africa Foundation (2023). He has co-organized two international workshops and conferences since 2022. He is a member of the Laboratory of Engineering Mathematics at Tunisia Polytechnic School, University of Carthage, Tunisia. Besides, he is a member of international member of laboratoire Artificial Intelligence Research and Applications (AIRA), Hassan I University, Settat, Morocco. H-index: 19; Total citations: 721; Expertise: Time scales, Dynamical Systems, Time delay systems, Neural Networks, Model Predictive Control. Imene Ouali is a researcher in Computer Science with a specialization in signal and image processing technologies. Her work spans multiple advanced fields, including Artificial Intelligence (AI), Augmented Reality (AR), and Ontology. She has contributed to cutting-edge research and development, integrating these technologies to solve complex problems in various domains. With a strong academic background and extensive experience in AI-driven applications, Dr. Ouali focuses on developing innovative solutions that bridge theoretical advancements and practical implementations. Her expertise also extends to interdisciplinary projects, where she explores the synergy between intelligent systems, data analysis, and emerging technologies. Achraf Wali is a doctoral student in Computer Science at the University of Sfax. His research focuses on the Internet of Things (IoT), artificial intelligence (AI), and business intelligence (BI) applications. He earned a bachelor's degree in Computer Science and Multimedia, followed by a research master's degree in Big Data, both from the University of Sfax. Additionally, he completed exchange programs at the University of Riga (Latvia) and the University of Palma de Mallorca (Spain), where he achieved distinguished academic results and gained practical experience in various research areas. Furthermore, he has completed several internships with national and international companies. He has also presented his work at international conferences. In addition, he is proficient in multiple languages, including English.

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