Global energy demand is expected to grow 47% by 2050, with oil remaining the number one source of energy. Renewables make up 27% of the global energy mix, as predicted by the International Energy Agency (IEA). To achieve IEA’s 2050 Net Zero targets, the electricity sector needs to reduce global emissions by nearly three-quarters. Even though renewables installations are expanding quickly, there is not enough to satisfy a strong rebound in global electricity demand. This will result in a sharp rise in the use of fossil fuel electricity generation that risks pushing carbon dioxide emissions. This book presents a comprehensive overview of energy efficiency, alternative energy resources, and process optimization for future sustainability.

The interplay between economic growth and sustainable development is a recurring theme, with discussions centering around the potential effects of nutrition on developmental outcomes. Optimizing Energy Efficiency During a Global Energy Crisis is a comprehensive and scholarly examination of the factors influencing economic development and their implications. This book delves into the multifaceted aspects of economic growth, encompassing social, political, cultural, and most notably, economic dimension to heighten awareness about their effects and consequences. The book also offers insights into investment policies and their implications for industrial business organizations, as well as the intricate dynamics of the health insurance market. Drawing upon diverse fields of study such as economy, development, informatics, and policy, this book offers a wide range of topics and methodologies to enrich the existing literature. It seeks to address the gaps in understanding and unexplored territories within these domains by employing original research and innovative approaches. This book is a valuable resource for scholars, researchers, and professionals in the fields of economics, finance, and development strategies. With an academic approach, this book will appeal to those seeking a deeper understanding of the complex interactions between economic factors and their consequences. It is particularly relevant for individuals involved in related markets and industries, offering practical insights and knowledge for informed decision-making.

In this era where data and voice services are available at a push of a button, service providers have virtually limitless options for reaching their customers with value-added services. The changes in services and underlying networks that this always-on culture creates make it essential for service providers to understand the evolving business logi

"The Evolution of Telecommunications: From Analog to Digital and Beyond" is an in-depth exploration of the telecommunications industry, tracing its history from the earliest forms of communication to the cutting-edge technologies that define the modern era. Written by Ron Legarski, a seasoned expert with over two decades of experience in the field, this book offers a comprehensive analysis of the technological advancements, industry shifts, and global events that have shaped telecommunications over the years. The book delves into the transformation from analog to digital communication, the rise of the internet, and the ongoing development of 5G and beyond. It covers critical topics such as the impact of AI, IoT, and edge computing on telecommunications, the role of quantum communication in securing networks, and the challenges posed by global events like the COVID-19 pandemic. In addition to historical context, "The Evolution of Telecommunications" provides detailed case studies of major companies and innovations, examining how industry leaders like AT&T, Verizon, and Nokia have navigated the changing landscape. It also explores the societal implications of telecommunications, including its role in driving economic growth, improving quality of life, and addressing global challenges like climate change and digital inclusion. With detailed appendices that include a glossary of key terms, a timeline of significant developments, and additional resources for further study, this book serves as both a comprehensive guide and a valuable reference for professionals, students, and anyone interested in the future of telecommunications. Whether you’re a telecommunications professional, a technology enthusiast, or simply curious about how the world stays connected, "The Evolution of Telecommunications" offers a thorough understanding of the forces that continue to shape our increasingly digital world.

A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.