Smart cities emanate from a smart renewable-energy-aided power grid. The smart grid technologies offer an array of benefits like reliability, availability, and resiliency. Smart grids phenomenally contribute to facilitating cities reaching those sustainability goals over time. Digital technologies, such as the Internet of Things (IoT), automation, artificial intelligence (AI) and machine learning (ML) significantly contribute to the two-way communication between utilities and customers in smart cities. Five salient features of this book are as follows: Smart grid to the smart customer Intelligent computing for smart grid applications Novel designs of IoT systems such as smart healthcare, smart transportation, smart home, smart agriculture, smart manufacturing, smart grid, smart education, smart government, smart traffic management systems Innovations in using IoT and AI in improving resilience of smart energy infrastructure Challenges and future research directions of smart city applications

Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems

Written and edited by a team of experts in the field, this groundbreaking new volume from Wiley-Scrivener offers the latest trends, processes, and breakthroughs in biomass and solar-powered technologies aimed at marching toward sustainable digital cities. This exciting new volume includes the research contribution of experts in solar and biomass-powered digital cities, incorporating sustainability by embedding computing and communication in day-to-day smart city applications. This book will be of immense use to practitioners in industries focusing on adaptive configuration and optimization in smart city systems. A wide array of smart city applications is also discussed with suitable use cases. The contributors to this book include renowned academics, industry practitioners, and researchers. Through case studies, it offers a rigorous introduction to the theoretical foundations, techniques, and practical solutions in this exciting area. Building smart cities with effective communication, control, intelligence, and security is discussed from societal and research perspectives. Whether for the veteran engineer, new hire, or student, this is a must-have volume for any library.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

This book explains the application of Artificial Intelligence and Internet of Things on green energy systems. The design of smart grids and intelligent networks enhances energy efficiency, while the collection of environmental data through sensors and their prediction through machine learning models improve the reliability of green energy systems.

Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).

Energy Harvesting: Enabling IoT Transformations gives insight into the emergence of energy harvesting technology and its integration with IoT-based applications. The book educates the reader on how energy is harvested from different sources, increasing the effectiveness, efficiency and lifetime of IoT devices. • Discusses the technology and practices involved in energy harvesting for biomedical, agriculture and automobile industries • Compares the performance of IoT-based devices with and without energy harvesting for different applications • Studies the challenges and issues in the implementation of EH-IoT • Includes case studies on energy-harvesting approach for solar, thermal and RF sources • Analyzes the market and business opportunities for entrepreneurs in the field of EH-IoT. This book is primarily aimed at graduates and research scholars in wireless sensor networks. Scientists and R&D workers in industry will also find this book useful.