This book aims to provide a vision that can combine the best of both Artificial Intelligence (AI) and communication networks for designing the deployment trajectory to establish flexible Unmanned Aerial Vehicles (UAV) communication networks.This book will discuss the major challenges that can face deploying unmanned aerial vehicles in emergent networks. It will focus on possible applications of UAV in a Smart City environment where they can be supported by Internet of Things (IoT), wireless sensor networks, as well as 5G, and beyond. This book presents the possible problems and solutions, the network integration of the UAV and compare the communication technologies to be used.This book will be a collection of original contributions regarding state of the art AI/ML based solutions in UAV communication networks which can be used for routing protocol design, transport layer optimization, user/application behaviour prediction, communication network optimization, security, and anomaly detection.

This book aims to provide a vision that can combine the best of both Artificial Intelligence (AI) and communication networks for designing the deployment trajectory to establish flexible Unmanned Aerial Vehicles (UAV) communication networks. This book will discuss the major challenges that can face deploying unmanned aerial vehicles in emergent networks. It will focus on possible applications of UAV in a Smart City environment where they can be supported by Internet of Things (IoT), wireless sensor networks, as well as 5G, and beyond. This book presents the possible problems and solutions, the network integration of the UAV and compare the communication technologies to be used. This book will be a collection of original contributions regarding state of the art AI/ML based solutions in UAV communication networks which can be used for routing protocol design, transport layer optimization, user/application behaviour prediction, communication network optimization, security, and anomaly detection.

This book sheds light on the cyber security challenges associated with nextgeneration computing technologies, emphasizing the serious threats posed to individuals, businesses, and nations. With everything becoming increasingly interconnected via the Internet, data security becomes paramount. As technology advances, people need to secure their data communication processes. Personal data security, including data integrity and confidentiality, is particularly vulnerable. Therefore, the concept of cyber security forensics emerges to ensure data security for everyone, addressing issues such as data control, hijacking, and threats to personal devices such as mobile phones, laptops, and other smart technologies. This book covers key topics related to cyber security in next-generation computing technologies, ultimately enhancing the quality of life for citizens, facilitating interaction with smart governments, and promoting secure communication processes. KEY FEATURES Highlights innovative principles and practices using next generation computing technologies based cybersecurity Presents an introduction to recent trends regarding the convergence of AI/ML in cybersecurity Offers an overview of theoretical, practical, simulation concepts of cybersecurity

This book constitutes the refereed post-conference proceedings of the 24th International Conference on Distributed and Computer and Communication Networks, DCCN 2021, held in Moscow, Russia, in September 2021. The 26 revised full papers and 3 revised short papers were carefully reviewed and selected from 151 submissions. The papers cover the following topics: computer and communication networks; analytical modeling of distributed systems; and distributed systems applications.

This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.

This book constitutes the proceedings of the 7th International Conference on Interactive Collaborative Robotics, ICR 2022, held in Fuzhou, China, in December 2022. The 25 papers presented were carefully reviewed and selected from 45 submissions. Challenges of human-robot interaction, robot control and behavior in social robotics and collaborative robotics, as well as applied robotic and cyber-physical systems are mainly discussed in the papers.

The book discusses how Unmanned Aerial Vehicles (UAVs) can leverage the sub-6 GHz massive MIMO to address cell selection and interference issues in future wireless networks. The book takes a close look at utilizing UAVs to achieving direct and efficient device-to device (D2D) communications in the sky. Also, the key 6G enablers (cell-free architectures, artificial intelligence, reconfigurable intelligent surfaces, THz communications, and non-terrestrial networks) for UAV communication are broached, and the primary technological challenges of each enabler are discussed extensively. Furthermore, the book covers the design of adaptable UAVs to operate in diverse and harsh environmental conditions. Additionally, the existing UAVs’ networking protocols and how these can be greatly enhanced to address the issue of intermittent network changes and channel impairments are discussed. The prospects and societal benefits envisioned in future UAVs are also presented.

The book presents theoretical and experimental approaches, quantitative and qualitative analyses, and simulations in wireless ad-hoc and sensor networks. It further explains the power and routing optimization in underwater sensor networks, advanced cross-layer framework, challenges and security issues in underwater sensor networks, and the use of machine learning and deep learning techniques for security implementations in wireless ad-hoc and sensor networks. This book: Discusses mobile ad-hoc network routing issues and challenges with node mobility and resource limitations. Covers the internet of vehicles, autonomous vehicle architecture, and design of heterogeneous wireless sensor networks. Presents various technologies of ad-hoc networks, use of machine learning, and deep learning techniques in wireless sensor networks. Illustrates recent advancements in security mechanisms for information dissemination in mobile ad-hoc networks, vehicular ad-hoc networks, flying ad-hoc networks, and autonomous vehicles. Highlights mathematical modeling and analysis of routing protocols for ad-hoc networks and underwater sensor networks. It is primarily written for undergraduate and graduate students, researchers, and academicians in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communications engineering.

The book titled "Applications of Computational Intelligence Techniques in Communications" is a one-stop platform for the researchers, academicians, and people from industry to get a thorough understanding of the latest research in the field of communication engineering. Over the past decade, a manyfold increase in the use of computational intelligence techniques has been identified for obtaining the most optimal and timely solution to a problem. The various aspects covering the significant contribution of numerous computational intelligence techniques have been discussed in detail in this book. Today’s era of machine learning and Internet of Things (IoT) is demanding as high as possible data rate which has resulted into tremendous increased speed of communication. To match-up the pace, the computational intelligence is posing to be the most efficient and favourite tool. The book aims to cover the current technological advancements in the field of communication engineering and give a detailed prospect of computational intelligence to its readers. This book will be a great support to the people working in the field of IoT, machine learning, healthcare, optimization, filter design, 5G and beyond, signal processing etc. The chapters included here will expose its audience to various newly introduced and advanced computational intelligence techniques applicable in communication domain. The readers will be exposed multiple interdisciplinary areas of research in communication and will get the motivation to work in collaboration with other professionals from both the academia and industry.