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Comprehensive resource describing both fundamentals and practical industry applications of antennas and radio propagation employed in modern wireless communication systems The newly revised and thoroughly updated Third Edition of this classic and popular text, Antennas and Propagation for Wireless Communication Systems addresses fundamentals and practical applications of antennas and radio propagation commonly used in modern wireless communication systems, from the basic electromagnetic principles to the characteristics of the technology employed in the most recent systems deployed, with an outlook of forthcoming developments in the field. Core topics include fundamental electromagnetic principles underlying propagation and antennas, basic concepts of antennas and their application to specific wireless systems, propagation measurement, modelling, and prediction for fixed links, macrocells, microcells, femtocells, picocells, megacells, and narrowband and wideband channel modelling with the effect of the channel on communication system performance. Worked examples and specific assignments for students are presented throughout the text (with a solutions manual available for course tutors), with a dedicated website containing online calculators and additional resources, plus details of simple measurements that students can perform with off-the-shelf equipment, such as their laptops and a Wi-Fi card. This Third Edition of Antennas and Propagation for Wireless Communication Systems has been thoroughly revised and updated, expanding on and adding brand new coverage of sample topics such as: Maxwell’s equations and EM theory, multiple reflections as propagation mechanisms, and waveguiding HAPS (High Altitude Platforms) propagation, design and noise considerations of earth stations, macrocell models, and cellular base station site engineering FSS (frequency selective surfaces), adaptive antenna theory developments (massive and distributed MIMO in particular), and how to process raw data related to channel measurements for mobile radio systems The techniques used in mobile systems spanning the latest 4G, 5G and 6G technology generations A wider range of frequencies, extending from HF, VHF and UHF up to the latest millimetre wave and sub terahertz bands With comprehensive coverage of foundational subject matter as well as major recent advancements in the field, Antennas and Propagation for Wireless Communication Systems is an essential resource for undergraduate and postgraduate students, researchers, and industry engineers in related disciplines.
TAGLINE Securing the Future of IoT with Advanced Edge Computing Solutions KEY FEATURES ● Tailored security protocols for edge computing, ensuring comprehensive protection against cyber threats. ● Master strategies for deploying, monitoring, and securing edge devices to maintain a resilient IoT ecosystem. ● Gain valuable insights from real-world examples, guiding you through the implementation of secure edge computing solutions across diverse industries. DESCRIPTION Embark on a journey into the cutting-edge world of secure edge computing. In this meticulously crafted handbook, delve deep into the intricacies of this transformative technology that is reshaping the landscape of computing. From its fundamental principles to advanced applications, this book leaves no stone unturned in demystifying the complexities of secure edge computing. Explore the architecture that underpins this paradigm shift, unraveling how it seamlessly integrates cloud resources with local devices to enhance efficiency and reliability. Dive into the nuances of security in edge computing, understanding the unique challenges posed by distributed networks and diverse endpoints. Learn essential strategies for safeguarding data integrity, confidentiality, and availability in this dynamic environment, ensuring robust protection against emerging threats. Discover real-world case studies and best practices from industry experts, gaining invaluable insights into deploying and managing secure edge computing solutions across various domains. With clear explanations, practical examples, and actionable advice, Secure Edge Computing For IoT empowers you to harness the full potential of this transformative technology while fortifying your digital infrastructure against evolving security risks. Prepare to embark on a journey of innovation and resilience at the edge of tomorrow’s computing landscape. WHAT WILL YOU LEARN ● Understand routing protocols and communication strategies tailored for edge environments. ● Implement measures to fortify edge infrastructure against cyber threats and safeguard sensitive data. ● Leverage real-time insights for informed decision-making and innovation. ● Integrate ML algorithms to enhance edge capabilities and optimize operations. ● Ensure reliability, scalability, and compliance with industry standards. ● Gain practical insights into the development process, from design to deployment. ● Protect edge infrastructure with encryption, authentication, and intrusion detection. ● Adhere to regulations and best practices in edge computing to ensure regulatory compliance and data privacy. ● Understand the components and architecture that underpin edge computing ecosystems. ● Explore practical examples and use cases from various industries to illustrate best practices and challenges in implementing secure edge computing solutions. WHO IS THIS BOOK FOR? This book is tailored for a diverse audience of IT professionals seeking to deepen their understanding of secure edge computing. It is particularly beneficial for DevOps engineers, system administrators, cloud architects, IoT developers, data analysts, and cybersecurity specialists. TABLE OF CONTENTS 1. Introduction to IoT and Edge Computing 2. Edge Computing Fundamentals and Use Cases 3. Edge Networking and Routing Protocols 4. IoT and Edge Computing Security 5. Data Analytics and Machine Learning at Edge 6. Secure Edge Design and Development 7. Secure Edge Penetration Testing and Incident Management 8. Edge Computing Cybersecurity and Cryptography 9. Cloud Computing in the Context of Edge Computing 10. Secure Edge Development and Implementation Index
The text comprehensively discusses machine-to-machine communication in real-time, low-power system design and estimation using field programmable gate arrays, PID, hardware, accelerators, and software integration for service applications. It further covers the recent advances in embedded computing and IoT for healthcare systems. The text explains the use of low-power devices such as microcontrollers in executing deep neural networks, and other machine learning techniques. This book: Discusses the embedded system software and hardware methodologies for system-on-chip and FPGA Illustrates low-power embedded applications, AI-based system design, PID control design, and CNN hardware design Highlights the integration of advanced 5G communication technologies with embedded systems Explains weather prediction modeling, embedded machine learning, and RTOS Highlights the significance of machine-learning techniques on the Internet of Things (IoT), real-time embedded system design, communication, and healthcare applications, and provides insights on IoT applications in education, fault attacks, security concerns, AI integration, banking, blockchain, intelligent tutoring systems, and smart technologies It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, and computer engineering.
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The intersection of artificial intelligence (AI) and digital twin technology presents a problem and an unparalleled opportunity for transformation. Businesses grapple with the need for operational excellence, innovation, and a competitive edge, all while navigating the intricate web of data analytics, decision-making, and real-time monitoring. In response to these challenges, Harnessing AI and Digital Twin Technologies in Businesses emerges as an example of insight and guidance, offering a comprehensive exploration of the complementary connection between AI and digital twin technology. In a world where the convergence of these powerful tools transforms business intelligence, enabling initiative-taking decision-making and dynamic simulations. This book serves as a solution for decision-makers, technologists, and researchers seeking to not only understand but harness the potential of AI-powered digital twins to enhance productivity, creativity, and judgment in their operations.
Deep Learning Models on Cloud Platforms provides an in-depth exploration of the integration of deep learning techniques with cloud computing environments. Architectures, and frameworks for developing and deploying deep learning models at scale. It addresses practical considerations, including data management, computational resources, and cost-efficiency, while highlighting popular cloud platforms like AWS, Google Cloud, and Azure. Through real-world examples and case studies, readers will gain insights into best practices for leveraging cloud infrastructure to enhance deep learning capabilities and drive innovation across various industries.
The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development.
With a growing population and increased mobility, global societies are facing the urgent need to transition to sustainable transportation solutions. However, the widespread adoption of electric vehicles (EVs) is hindered by challenges, from limitations in battery technology to the scarcity of charging infrastructure. These obstacles impede progress toward a cleaner future and limit EVs' potential economic and social benefits. Solving Fundamental Challenges of Electric Vehicles offers a comprehensive roadmap to navigate the complexities of EV adoption. It delves into critical issues such as battery technology advancements, charging infrastructure development, and policy and regulatory frameworks. The book empowers stakeholders to overcome these challenges and accelerate the transition to electric mobility by providing insights into innovative solutions and breakthrough technologies.
In the dynamic realm of agriculture, artificial intelligence (AI) and machine learning (ML) emerge as catalysts for unprecedented transformation and growth. The emergence of big data, Internet of Things (IoT) sensors, and advanced analytics has opened up new possibilities for farmers to collect and analyze data in real-time, make informed decisions, and increase efficiency. AI and ML are key enablers of data-driven farming, allowing farmers to use algorithms and predictive models to gain insights into crop health, soil quality, weather patterns, and more. Agriculture is an industry that is deeply rooted in tradition, but the landscape is rapidly changing with the emergence of new technologies. Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture is a comprehensive guide that explores how the latest advances in technology can help farmers make better decisions and maximize yields. It offers a detailed overview of the intersection of data, AI, and ML in agriculture and offers real-world examples and case studies that demonstrate how these tools can help farmers improve efficiency, reduce waste, and increase profitability. Exploring how AI and ML can be used to achieve sustainable and profitable farming practices, the book provides an introduction to the basics of data-driven farming, including an overview of the key concepts, tools, and technologies. It also discusses the challenges and opportunities facing farmers in today’s data-driven landscape. Covering such topics as crop monitoring, weather forecasting, pest management, and soil health management, the book focuses on analyzing data, predicting outcomes, and optimizing decision-making in a range of agricultural contexts.