Internet of Things (IoT) – An Engineering Approach: From Principles to Practice provides clear engineering practice guides on developing intelligent sensor/actuator nodes and then forming an IoT system, without the confusion of network/communication protocols.IoT will be widely used in smart homes, smart cities, digital health, and digital manufacturers. However, the development of an IoT system can be complicated since it combines technologies in networking and security, wireless communication, broadband cellular networks, sensors and actuators, data acquisition and real-time embedded systems, edge computing with artificial intelligence, and low-power electronics technologies.All engineering practice topics come with examples mostly from the first-hand materials of the author’s research projects, e.g. digital switching, powering indoor IoT sensor nodes by photovoltaic energy harvesting, laser sensors for greenhouse plant, low-power electronics for implantable neural recording for blowfly, zero-power passive sensing, MEMs capacitor for ultrasound imaging/digital speaker, contactless electrode for physiological measurements, EoG based gaze tracking for augmented reality. Therefore, this book can be used for teaching or used as a reference for relevant research.
Explainable AI in Healthcare Imaging for Medical Diagnoses: Digital Revolution of AI presents the most advanced machine learning and deep learning methodologies in the healthcare domain, with specific focus on learning explainable artificial intelligence (XAI).This book explores how XAI can make improvements in the medical sector to improve trust for end users. Covering the most advanced and emerging concepts and applications of XAI, researchers, practitioners, and students in the fields of biomechanical engineering, electrical engineering, and computer engineering will find this to be a great source of information for this emerging topic.
State-of-the-Art Geothermal Well Drilling Case Studies provides updated information on technological advances and research on the state-of-the-art performance of recent geothermal wells drilled for energy in the global push to reduce greenhouse gases. The book provides advances in a rapidly growing market that has adopted and adapted oilfield technologies to rapid scale development and production as demonstrated through global examples in a case-study format. Different geologic formations and well trajectories require different drilling tools and drilling parameters to yield optimum results.Showcasing current examples of successful global geothermal well-drilling applications, this text provides readers, researchers, and industry professionals with the keys needed to rapidly scale geothermal drilling operations, a clean and abundant source of energy that supports sustainability and reduction of carbon emissions.
Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces readers to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring.This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies.
The Role of Green and Transition Finance in Achieving Carbon Neutrality and Sustainable Energy presents a holistic overview of this essential, often-overlooked aspect of energy transition, led by one of the foremost experts on the topic. Beginning with a clear outline of the fundamentals, this book equips readers with an understanding of the instruments and mechanisms supporting financial markets in general and the energy market in particular, such as ESG factors. It moves on to present market strategies for encouraging and supporting sustainable, green, and net-zero advances. Finally, it present tools, viewpoints, and case studies from diverse and global perspectives, enabling readers to design policy, model outcomes, and monitor effectiveness. Building from a basic theoretical framework to practical, complex country-level scenarios, The Role of Green and Transition Finance in Achieving Carbon Neutrality and Sustainable Energy is an essential resource for students, policy makers, and researchers in energy markets.
Necrobotics for Healthcare Applications and Management delves into the emerging area of necrobotics and its implications for healthcare. Exploring the convergence of robotics, technology, and healthcare, the book presents leading-edge research, practical implementations, and ethical considerations. It bridges a significant gap in healthcare literature, furnishing a contemporary and comprehensive perspective on necrobotics. Highlighting its distinct applications, management nuances, and ethical dimensions in the domain of medical robotics, the book equips readers with an in-depth grasp of this evolving field. It offers insights into technological intricacies, practical utilization, and ethical guidelines. Through real-world case studies and exemplar practices, it vividly demonstrates successful necrobotics deployments while addressing integration challenges. The book facilitates adept navigation of necrobotics complexities, spur innovation, enhance patient outcomes, and contribute to healthcare evolution. Catering to the distinct information requisites and daily obstacles encountered by engineers, healthcare practitioners, and researchers, the book offers extensive insights into necrobotics technologies, real-life case studies, and ethical reflections. It stands as a valuable resource for individuals striving to harness necrobotics' potential for efficacious healthcare solutions.
Climate and Natural Hazard Risks is an in-depth examination of the physical, environmental, economic, and social impacts of climate change and natural hazards on vulnerable populations in different areas around the world. The authors open with the simple question “what is risk?,” taking a detailed look at global trends and risk frameworks as they relate to climate change. From there, the chapters systematically review different hazards and their implications for risk and resilience (hurricanes, cyclones, flooding, extreme temperatures, food insecurity, earthquakes, tsunamis). The authors then delve into the latest research and data surrounding probabilistic hazard assessment and multi-hazard risk assessment. The book closes with a thoughtful discussion on resilience and the wide-reaching impacts of environmental transitions. Professionals working across climate change, environmental risk assessment, and disaster resilience will find much to consider in this thought-provoking text.
Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. The book includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. It delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth Observation.This is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.
Harnessing Automation and Machine Learning for Resource Recovery and Value Creation. From Waste to Value provides a comprehensive understanding of how automation and machine learning technologies can be used to convert waste into valuable resources. The book gives insight in the opportunities offered by automation and machine learning technologies in waste management and how they can help address the challenges associated with waste management and to discuss the benefits and potential of automation technologies. It examines the potential of machine learning algorithms in analyzing waste management data, identifying patterns, predicting future waste generation, and optimizing waste management processes. Moreover, the book showcases case studies from different industries and regions, highlighting the revolutionary applications of automation and machine learning in waste management. Harnessing Automation and Machine Learning for Resource Recovery and Value Creation. From Waste to Value is an indispensable resource for researchers, waste management professionals, policymakers interested in learning more about how automation and machine learning can contribute to waste management and the creation of a sustainable future.
The integration of ground-breaking technologies, such as next-generation batteries and AI-powered systems, promises to reshape the way we commute, transport goods, and navigate our cities. Autonomous Electric Vehicles: Nonlinear Control, Traction, and Propulsion offers sought-after, specialized know-how on robotized electric vehicles (ground, surface, underwater, aerial). The book builds on theoretical fundamentals to then comprehensively cover the very latest research advances in nonlinear control, estimation, and fault diagnosis for autonomous navigation and electric traction systems. Part I investigates nonlinear optimal control and estimation of a specific class of vehicle per chapter, while part II control and dynamic modeling of a specific type of electric motor per chapter. Furthermore, the methodological analysis conducted is not constrained by the shortcomings of global linearization-based control algorithms, is computationally easy to implement, and is also corroborated by global robustness and stability proofs. Case studies and other practical application discussions exemplify these methods’ potential prospects if adopted at commercial scale. Readers from a wide range of related disciplines will benefit from the structured, modular approach of the volume, which was written by a group of experts with backgrounds both in academia and industry, whose aim is also to contribute transformative solutions to accelerate the global low-carbon power transition as well as smart energy management systems for the continuing shift to renewables.