Explore the intersection between unmanned aerial vehicles (UAVs) and the evolving landscape of smart cities. With the increasing integration of technology into urban environments, there is a growing need to understand how UAV swarms can contribute to the safety, efficiency, and resilience of these complex urban ecosystems. The book aims to provide a technical understanding of UAV swarms and their applications within the context of smart cities.
It begins by laying the groundwork with an introduction to UAV swarms and smart cities, establishing the foundational concepts and motivations behind their integration. As the book progresses, it delves into various aspects of smart cities, exploring concepts, technologies, and challenges inherent in their development and operation. This includes discussions on cloud computing, cybersecurity, machine learning applications, surveillance and monitoring systems, urban planning, and infrastructure management. It also examines the integration of IoT devices with UAV swarms, highlighting the synergies between these emerging technologies and their potential impact on urban environments.
The book examines cutting-edge topics such as edge computing, blockchain applications, 5G integration, and augmented reality/virtual reality (AR/VR) visualization techniques in the context of UAV swarm operations. It concludes with reflections on innovations and future directions, offering insights into the evolving landscape of UAV swarm technologies and their implications for the protection and advancement of smart cities.
The book serves as a comprehensive guide for researchers, practitioners, and policymakers interested in understanding the technical, social, and economic dimensions of UAV swarm technology within the context of smart city development and management.
What You Will Learn
Identify practical applications of UAV swarms in surveillance monitoring, urban planning, disaster management, and infrastructure resilience
Gain comprehensive understanding of UAV swarms by exploring diverse disciplines
Apply insights from emerging technologies like cloud computing, machine learning, blockchain, IoT devices, and so on to UAV swarm technology
Who Is This Book For
This book appeals to a wide range of readers with different interests and backgrounds, including researchers, policymakers, industry stakeholders, practitioners, experts, and general fans who are curious in the confluence of smart cities with UAV swarm technologies with little to no experience or knowledge of UAV swarms.
Oroos Arshi is a Research Scientist at AI-EYS and was awarded the Young Researcher award at the International Conference on Emerging Trends and Innovations (ICETI) 2024 held in Pakistan. She is a dedicated Research Scholar at the University of Petroleum and Energy Studies in Dehradun, India. She was the speaker at the International Conference on Emerging Trends and Innovations held in Pakistan. She has contributed significantly to the technological discourse with some Scopus, SCI, and a noteworthy publication with Springer. Since then, Oroos has embarked on an intricate exploration of diverse technological realms, displaying a profound interest in the Natural Processing Language (NLP), Computer Vision, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, and Cloud Computing.
Dr. Inam Ullah Khan is the Founder of AI-EYS. He was a visiting researcher at King’s College London, UK and was a faculty member at different universities in Pakistan including the Center for Emerging Sciences Engineering & Technology (CESET), Islamabad, Abdul Wali Khan University, Garden Campus, Timergara Campus, University of Swat & Shaheed Zulfikar Ali Bhutto Institute of Science and Technology (SZABIST), Islamabad Campus. He has authored/co-authored more than 30 research articles in reputable journals, conferences, and book chapters. His research interests include Network System Security, Intrusion Detection, Intrusion Prevention, cryptography, Optimisation techniques, WSN, IoT, Mobile Ad Hoc Networks (MANETS), Flying Ad Hoc Networks, and Machine Learning. He was a technical program committee member at an international workshop on intelligent systems for sustainable smart cities, New Delhi, India, February 19–20, 2022.
Keshav Kaushik is an experienced educator with around ten years of teaching and research experience in Cybersecurity, Digital Forensics, and the Internet of Things. He is working as an Assistant Professor (Senior Scale) in the systemic cluster under the School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. He has published 100+ research papers in International Journals and has presented at reputed International Conferences. Currently, he is also serving as à Vice Chairperson of the Meerut ACM Professional Chapter and is also a brand ambassador for Bentham Science.
Nadeem Iqbal (Senior Member IEEE) received a Ph.D. degree in bio and brain engineering from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, in 2013. He has completed a Fulbright Fellowship at St. John’s University in New York, USA. Dr. Iqbal was a postdoctoral fellow at the School of Mechanical Engineering, University of Leeds, UK. He is currently working as an Associate Professor with the Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan. His research interests include biological information processing mechanisms in the brain, Natural Language Processing, the Internet of Things, and Pattern recognition.
Inam Ullah received a B.Sc. degree in Electrical Engineering (Telecommunication) from the Department of Electrical Engineering, University of Science and Technology Bannu (USTB), KPK, Pakistan, in 2016 and a Master's and Ph.D. degree in Information and Communication Engineering from the College of Internet of Things (IoT) Engineering, Hohai University (HHU), China, in 2018 and 2022, respectively. He is currently an Assistant Professor at the Department of Computer Engineering, Gachon University, S Korea. His research interests include Robotics, Internet of Things (IoT), Wireless Sensor Networks (WSNs), Underwater Communication and Localization, Underwater Sensor Networks (USNs), Artificial Intelligence (AI), Big data, Deep learning, etc. He has authored more than 70 peer-reviewed articles on various research topics.
Dr. Khadija Slimani completed her PhD, which was jointly supervised by the University of Ibn Tofail in Morocco and the University of Technology of Belfort Montbeliard (UTBM) in France. This collaborative international effort showcased her commitment to academic excellence and cross-cultural research. For her doctoral studies, Dr. Slimani delved into the realms of machine learning, deep learning, pattern recognition, and computer vision, with a specific focus on academic emotion recognition. This interdisciplinary approach, spanning both Moroccan and French academic environments, enriched her research experience and contributed to the global perspective of her work. Dr. Slimani's academic contributions extended to various engineering schools in Paris, France, where she took on teaching responsibilities across multiple modules, including data science, deep learning, machine learning, data bases, and computer vision. She currently holds the title of Associate Professor at the Graduate School of Automatic Electronic Computing in Paris, France. Through her diverse roles, Dr. Slimani consistently inspires and contributes to shaping the next generation of researchers.
