With the advancement in computing technologies, the need for power is also increasing. Approximately 3% of the total power consumption is spent by data centers and computing devices. This percentage will rise when more internet of things (IoT) devices are connected to the web. The handling of this data requires immense power. Energy Systems Design for Low-Power Computing disseminates the current research and the state-of-the-art technologies, topologies, standards, and techniques for the deployment of energy intelligence in edge computing, distributed computing, and centralized computing infrastructure. Covering topics such as electronic cooling, stochastic data analysis, and energy consumption, this premier reference source is an excellent resource for data center designers, VLSI designers, network developers, students and teachers of higher education, librarians, researchers, and academicians.

This book documents electric power requirements for the dismounted soldier on future Army battlefields, describes advanced energy concepts, and provides an integrated assessment of technologies likely to affect limitations and needs in the future. It surveys technologies associated with both supply and demand including: energy sources and systems; low power electronics and design; communications, computers, displays, and sensors; and networks, protocols, and operations. Advanced concepts discussed are predicated on continued development by the Army of soldier systems similar to the Land Warrior system on which the committee bases its projections on energy use. Finally, the volume proposes twenty research objectives to achieve energy goals in the 2025 time frame.

The Information and communication technology (ICT) industry is said to account for 2% of the worldwide carbon emissions – a fraction that continues to grow with the relentless push for more and more sophisticated computing equipment, c- munications infrastructure, and mobile devices. While computers evolved in the directionofhigherandhigherperformanceformostofthelatterhalfofthe20thc- tury, the late 1990’s and early 2000’ssaw a new emergingfundamentalconcern that has begun to shape our day-to-day thinking in system design – power dissipation. As we elaborate in Chapter 1, a variety of factors colluded to raise power-ef?ciency as a ?rst class design concern in the designer’s mind, with profound consequences all over the ?eld: semiconductor process design, circuit design, design automation tools, system and application software, all the way to large data centers. Power-ef?cient System Design originated from a desire to capture and highlight the exciting developments in the rapidly evolving ?eld of power and energy op- mization in electronic and computer based systems. Tremendous progress has been made in the last two decades, and the topic continues to be a fascinating research area. To develop a clearer focus, we have concentrated on the relatively higher level of design abstraction that is loosely called the system level. In addition to the ext- sive coverage of traditional power reduction targets such as CPU and memory, the book is distinguished by detailed coverage of relatively modern power optimization ideas focussing on components such as compilers, operating systems, servers, data centers, and graphics processors.

In today’s modern society, to reduce the carbon dioxide gas emission from motor vehicles and to save mother nature, electric vehicles are becoming more practical. As more people begin to see the benefits of this technology, further study on the challenges and best practices is required. Artificial Intelligence Applications in Battery Management Systems and Routing Problems in Electric Vehicles focuses on the integration of renewable energy sources with the existing grid, introduces a power exchange scenario in the prevailing power market, considers the use of the electric vehicle market for creating cleaner and transformative energy, and optimizes the control variables with artificial intelligence techniques. Covering key topics such as artificial intelligence, smart grids, and sustainable development, this premier reference source is ideal for government officials, industry professionals, policymakers, researchers, scholars, practitioners, academicians, instructors, and students.

The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.

In the environment of energy systems, the effective utilization of both conventional and renewable sources poses a major challenge. The integration of microgrid systems, crucial for harnessing energy from distributed sources, demands intricate solutions due to the inherent intermittency of these sources. Academic scholars engaged in power system research find themselves at the forefront of addressing issues such as energy source estimation, coordination in dynamic environments, and the effective utilization of artificial intelligence (AI) techniques. Intelligent Solutions for Sustainable Power Grids focuses on emerging research areas, this book addresses the uncertainty of renewable energy sources, employs state-of-the-art forecasting techniques, and explores the application of AI techniques for enhanced power system operations. From economic aspects to the digitalization of power systems, the book provides a holistic approach. Tailored for undergraduate and postgraduate students as well as seasoned researchers, it offers a roadmap to navigate the intricate landscape of modern power systems. Dive into a wealth of knowledge encompassing smart energy systems, renewable energy integration, stability analysis of microgrids, power quality enhancement, and much more. This book is not just a guide; it is the solution to the pressing challenges in the dynamic field of energy systems.

Very Large Scale Integration (VLSI) Systems refer to the latest development in computer microchips which are created by integrating hundreds of thousands of transistors into one chip. Emerging research in this area has the potential to uncover further applications for VSLI technologies in addition to system advancements. Design and Modeling of Low Power VLSI Systems analyzes various traditional and modern low power techniques for integrated circuit design in addition to the limiting factors of existing techniques and methods for optimization. Through a research-based discussion of the technicalities involved in the VLSI hardware development process cycle, this book is a useful resource for researchers, engineers, and graduate-level students in computer science and engineering.