This book provides an investigative approach to how machine learning is helping to maintain and secure smart cities, including principal uses such as smart monitoring, privacy, reliability, and public protection. The authors cover important areas and issues around implementation roadblocks, ideas, and opportunities in smart city development. The authors also include new algorithms, architectures and platforms that can accelerate the growth of smart city concepts and applications. Moreover, this book provides details on specific applications and case studies related to smart city infrastructures, big data management, and prediction techniques using machine learning.

With the increase in the development of the advanced cellular communication system, it is assumed that several sectors, such as the health industry, education, transport industry, business model, and so on, will rapidly grow. However, the requirements of the above-mentioned sectors are different and difficult to fulfill. Hence, 5G will be integral to several networks and will also need a unique management system for its successful rollout around the globe. 5G-Based Smart Hospitals and Healthcare Systems: Evaluation, Integration, and Deployment provides an overview of the role of advanced technologies in transforming the healthcare industry. It emphasizes the technical requirements of smart hospitals and the technologies associated with them along with explaining how technologies such as IoT, machine learning, and AI can be integrated with smart hospitals and 5G networks. The book evaluates several concerns such as privacy of data, infrastructure costs, and regular upgradability of technologies. Since the storage of information is a major concern with the implantation of 5G-based hospitals, this book will specifically address those issues along with examining the potential pitfalls of 5G-based hospitals and the factors that cause their failures. This book specifically targets professionals, academicians, engineers, researchers, management firms, technical institutes, R&D establishments, and individuals researching in the fields of 5G, healthcare, medical sensors, IoT, big data, and related fields. The main objectives of this book are to accumulate state-of-the-art IoT, 5G, AI, and machine learning-based approaches for resolving healthcare problems.

The Internet of Things (IoT) has numerous applications, including smart cities, industries, cloud-based apps, smart homes, and surveillance. The Internet of Things (IoT) enables smarter living by connecting devices, people, and objects. As networking became a crucial aspect of the Internet, rigorous design analysis led to the development of new research areas. The Internet of Things has revolutionized daily living in countless ways. It enables communication between buildings, people, portable gadgets, and vehicles, facilitating mobility. Smart cities and cloud-based data have transformed corporate practices. With billions of connected gadgets, everything will soon be able to communicate remotely. IoT networks, whether public or private, rely significantly on machine learning and software-defined networking. Indian and other governments have approved various research projects on IoT-based networking technologies. This field of study will significantly impact society in the future. Researchers are concerned about the many application areas and driving forces behind smart cities. The authors aim to provide insights into software-defined networking, artificial intelligence, and machine learning technologies used in IoT and networking. The framework focuses on practical applications and infrastructures. The book includes practical challenges, case studies, innovative concepts, and other factors that impact the development of realistic scenarios for smart surveillance. It also highlights innovative technology, designs, and algorithms that can accelerate the creation of smart city concepts. This resource includes real-world applications and case studies for smart city technology, enormous data management, and machine learning prediction, all with confidentiality and safety problems.

AI Applications to Communications and Information Technologies Apply the technology of the future to networking and communications. Artificial intelligence, which enables computers or computer-controlled systems to perform tasks which ordinarily require human-like intelligence and decision-making, has revolutionized computing and digital industries like few other developments in recent history. Tools like artificial neural networks, large language models, and deep learning have quickly become integral aspects of modern life. With research and development into AI technologies proceeding at lightning speeds, the potential applications of these new technologies are all but limitless. AI Applications to Communications and Information Technologies offers a cutting-edge introduction to AI applications in one particular set of disciplines. Beginning with an overview of foundational concepts in AI, it then moves through numerous possible extensions of this technology into networking and telecommunications. The result is an essential introduction for researchers and for technology undergrad/grad student alike. AI Applications to Communications and Information Technologies readers will also find: In-depth analysis of both current and evolving applications Detailed discussion of topics including generative AI, chatbots, automatic speech recognition, image classification and recognition, IoT, smart buildings, network management, network security, and more An authorial team with immense experience in both research and industry AI Applications to Communications and Information Technologies is ideal for researchers, industry observers, investors, and advanced students of network communications and related fields.

This book exploits the benefits of integration of wireless sensor networks (WSN) and Internet of Things (IoT) for smart cities. The authors discuss WSN and IoT in tackling complex computing tasks and challenges in the fields of disaster relief, security, and weather forecasting (among many others). This book highlights the challenges in the field of quality of service metrics (QoS) in the WSN based IoT applications. Topics include IoT Applications for eHealth, smart environments, intelligent transportation systems, delay tolerant models for IoT applications, protocols and architectures for industrial IoT, energy efficient protocols, and much more. Readers will get to know the solutions of these problems for development of smart city applications with the integration of WSN with IoT.

In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges of disasters and charts a path toward proactive solutions by applying artificial intelligence (AI) and machine learning (ML). This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four ‘R’s - Risk Mitigation, Response Readiness, Response Execution, and Recovery - as integral components of comprehensive disaster management. This book explores various AI and ML applications designed to predict, manage, and mitigate the impact of natural disasters, focusing on natural language processing, and early warning systems. The contrast between weak AI, simulating human intelligence for specific tasks, and strong AI, capable of autonomous problem-solving, is thoroughly examined in the context of disaster management. Its chapters systematically address critical issues, including real-world data handling, challenges related to data accessibility, completeness, security, privacy, and ethical considerations.

This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software-defined network. Also, this book provides a guide for researchers of IoT applications to choose suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges. Features: Explains machine learning algorithms onto low-power wide area network sensors for compressed communications. Illustrates wireless-based Internet of Things networks using low-power wide area networks technology for quality air. Presents cognitive Internet of Things networks using wireless communication, and low-power wide area network technologies for Ad Hoc networks. Discusses a comprehensive study of low-power wide area networks for flying Ad Hoc networks. Showcases the study of energy efficient techniques aided by low-power wide area network technologies for the Internet of Things networks. The text is aimed at senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.