Underwater wireless sensor networks (UWSN) are envisioned as an aquatic medium for a variety of applications including oceanographic data collection, disaster management or prevention, assisted navigation, attack protection, and pollution monitoring. Similar to terrestrial wireless sensor networks (WSN), UWSNs consist of sensor nodes that collect the information and pass it to a base station; however, researchers have to face many challenges in executing the network in an aquatic medium. Energy-Efficient Underwater Wireless Communications and Networking is a crucial reference source that covers existing and future possibilities of the area as well as the current challenges presented in the implementation of underwater sensor networks. While highlighting topics such as digital signal processing, underwater localization, and acoustic channel modeling, this publication is ideally designed for machine learning experts, IT specialists, government agencies, oceanic engineers, communication experts, researchers, academicians, students, and environmental agencies concerned with optimized data flow in communication network, securing assets, and mitigating security attacks.

"This book focuses on wireless sensor networks and their operation, covering topics including routing, energy efficiency and management"--

This reference text discusses intelligent robotic and drone technology with embedded Internet of Things (IoT) for smart applications. The text discusses future directions of optimization methods with various engineering and science fundamentals used in robotics and drone-based applications. Its emphasis is on covering deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. It covers important topics including sensors and actuators in the internet of things (IoT), internet-of-robotics-things (IoRT), IoT in agriculture and food processing, routing challenges in flying Ad-hoc networks, and smart cities. The book will serve as a useful text for graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and mechanical engineering.

This book constitutes selected papers presented at the First International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022, held as a virtual event in October 2022. The 69 papers were thoroughly reviewed and selected from the 258 subissions. The book focuses on current development in the fields of communication and intelligent systems.

Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection. - Reviews the different types of DTN and shows how they can be applied in satellite and deep-space communications, vehicular communications (including unmanned aerial), and during large-scale disasters - Considers security concerns for DTN and potential for rapid selection and dissemination of urgent messages - Reviews the breadth of areas in which DTN is already providing solutions - Covers the prospects for DTN's wider adoption and development of standards

This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. • Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. • Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. • Explores the importance of blockchain technology in the Internet of Things security issues. • Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. • Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications. This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.

During the last one and a half decades, wireless sensor networks have witnessed significant growth and tremendous development in both academia and industry. A large number of researchers, including computer scientists and engineers, have been interested in solving challenging problems that span all the layers of the protocol stack of sensor networking systems. Several venues, such as journals, conferences, and workshops, have been launched to cover innovative research and practice in this promising and rapidly advancing field. Because of these trends, I thought it would be beneficial to provide our sensor networks community with a comprehensive reference on as much of the findings as possible on a variety of topics in wireless sensor networks. As this area of research is in continuous progress, it does not seem to be a reasonable solution to keep delaying the publication of such reference any more. This book relates to the second volume and focuses on the advanced topics and applications of wireless sensor networks. Our rationale is that the second volume has all application-specific and non-conventional sensor networks, emerging techniques and advanced topics that are not as matured as what is covered in the first volume. Thus, the second volume deals with three-dimensional, underground, underwater, body-mounted, and societal networks. Following Donald E. Knuth’s above-quoted elegant strategy to focus on several important fields (The Art of Computer Programming: Fundamental Algorithms, 1997), all the book chapters in this volume include up-to-date research work spanning various topics, such as stochastic modeling, barrier and spatiotemporal coverage, tracking, estimation, counting, coverage and localization in three-dimensional sensor networks, topology control and routing in three-dimensional sensor networks, underground and underwater sensor networks, multimedia and body sensor networks, and social sensing. Most of these major topics can be covered in an advanced course on wireless sensor networks. This book will be an excellent source of information for graduate students majoring in computer science, computer engineering, electrical engineering, or any related discipline. Furthermore, computer scientists, researchers, and practitioners in both academia and industry will find this book useful and interesting.

MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

This book presents the proceedings of the 6th International Conference on Wireless Intelligent and Distributed Environment for Communication (WIDECOM 2023), which took place at Brock University, St. Catharines, Ontario, Canada, October 11-13, 2023. The book addresses issues related to new dependability paradigms, design, and performance of dependable network computing and mobile systems, as well as issues related to the security of these systems. The goal of the conference is to provide a forum for researchers, students, scientists and engineers working in academia and industry to share their experiences, new ideas and research results in the above-mentioned areas.