This book addresses and disseminates state-of-the-art research and development in the applications of intelligent techniques for smart grids and renewable energy systems. This helps the readers to grasp the extensive point of view and the essence of the recent advances in this field. The book solicits contributions from active researchers which include theory, case studies and intelligent paradigms pertaining to the smart grid and renewable energy systems. The prospective audience would be researchers, professionals, practitioners and students from academia and industry who work in this field.
Cyber-physical systems (CPS) have emerged as a unifying name for systems where cyber parts (i.e., the computing and communication parts) and physical parts are tightly integrated, both in design and during operation. Such systems use computations and communication deeply embedded in and interacting with human physical processes as well as augmenting existing and adding new capabilities. As such, CPS is an integration of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. Artificial Intelligence Paradigms for Smart Cyber-Physical Systems focuses on the recent advances in Artificial intelligence-based approaches towards affecting secure cyber-physical systems. This book presents investigations on state-of-the-art research issues, applications, and achievements in the field of computational intelligence paradigms for CPS. Covering topics that include autonomous systems, access control, machine learning, and intrusion detection and prevention systems, this book is ideally designed for engineers, industry professionals, practitioners, scientists, managers, students, academicians, and researchers seeking current research on artificial intelligence and cyber-physical systems.
Our book, Future of Tech Startups and Innovations in the Age of AI, mainly focuses on artificial intelligence (AI) tools, AI-based startups, AI-enabled innovations, Autonomous AI Agents (Auto-GPT), AI-based marketing startups, machine learning for organizations, AI-internet of things (IoT) for new tech companies, AI-enabled drones for agriculture industry, machine learning (ML)/deep learning (DL)-based drip farming, AI-based driverless cars, AI-based weather prediction startups, AI tools for personal branding, AI-based teaching, AI-based doctor/hospital startups, AI for game companies, AI-based finance tools, AI for human resource management, AI-powered management tools, AI tools for future pandemics, AI/ML-based transportation companies, AI for media, AI for carrier counseling, AI for customer care, AI for next generation businesses, and many more applications. AI tools and techniques will revolutionize startups all over the world. Entrepreneurs, engineers, and practitioners have already moved toward AI-based solutions to reshape businesses. AI/ML will create possibilities and opportunities for improving human lifestyles. AI-enabled startups will work on cost-effective solutions to solve difficult problems. Recently, many research companies are interested in providing solutions and investing a lot in AI-based startups. AI-driven products will revolutionize the "smart world." AI computing tech companies will help to model human speech recognition systems. Also, AI-based startups will focus on perception and reasoning of autonomous robotic systems. AI/ML-based tech startups will introduce smart online education systems for future pandemics. More interestingly, people are also moving for online job opportunities and trying to work from home. Future innovation needs closer relations between academia and industry. Therefore, online platforms need to be introduced that will only focus on academia and industry linkage. Future AI tech-based startups will focus more on research and development to introduce novel products to the market. Accordingly, engineers and many other people should be trained on AI tools and techniques to introduce innovative solutions for the smart world. In addition, integration of many new technologies with AI will be made possible. AI with IoT, smart cities, unmanned aerial vehicles (UAVs), wireless sensor networks, software-defined networks, network management, vehicular ad hoc networks, flying ad hoc networks, wireless communication technologies, ML, reinforcement learning, federated learning and other mechanisms will introduce new technological products.
Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems. Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students.
As the application of smart technologies for monitoring environmental activities becomes more widespread, there is a growing demand for solutions that can help analyze the risk factors and impacts on the environment by focusing on energy consumption, storage, and management. This book is designed to serve as a knowledge-sharing platform, focusing on the emerging models, architectures, and algorithms being developed for smart computational technologies that can lead to efficient energy conservation and environmental sustainability.
The volume is a collection of best selected research papers presented at the 4th International Conference on Inventive Material Science Applications (ICIMA 2021) organized by PPG Institute of Technology, Coimbatore, India during 14 – 15 May 2021. The book includes original research by material science researchers towards developing a compact and efficient functional elements and structures for micro, nano and optoelectronic applications. The book covers important topics like nanomaterials and devices, optoelectronics, sustainable electronic materials, nanocomposites and nanostructures, hybrid electronic materials, medical electronics, computational material science, wearable electronic devices and models, and optical/nano-sensors.
"This reference book covers the latest innovations and trends within smart grid and microgrid development, detailing benefits, challenges, and opportunities, that will help readers to fully understand the current opportunities that smart grids and microgrids present around the world"--
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source
This book focusses on power quality improvement and enhancement techniques with aid of intelligent controllers and experimental results. It covers topics ranging from the fundamentals of power quality indices, mitigation methods, advanced controller design and its step by step approach, simulation of the proposed controllers for real time applications and its corresponding experimental results, performance improvement paradigms and its overall analysis, which helps readers understand power quality from its fundamental to experimental implementations. The book also covers implementation of power quality improvement practices. Key Features Provides solution for the power quality improvement with intelligent techniques Incorporated and Illustrated with simulation and experimental results Discusses renewable energy integration and multiple case studies pertaining to various loads Combines the power quality literature with power electronics based solutions Includes implementation examples, datasets, experimental and simulation procedures
This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.
