Cyber Physical System (CPS) is an integration of computation, networking, and physical processes: the combination of several systems ofdifferent nature whose main purpose is tocontrol a physical process and, through feedback, adapt itself to new conditions, in real time.Cyber Physical System: Concepts and Applications includes an in-depth coverage of the latestmodels and theories that unify perspectives. It expresses the interacting dynamics of the computational and physical components of asystem in a dynamic environment. Covers automatic application of software countermeasures against physical attacks and impact of cyber physical system on industry 4.0 Explains how formal models provide mathematical abstractions to manage the complexity of a system design Offers a rigorous and comprehensive introduction to the principles of design,specification, modelling, and analysis of cyber physicalsystems Discusses the multiple domains where Cyber Physical system has a vital impact and provides knowledge about different models thatprovide mathematical abstractions tomanage the complexity of a system design Provides the rapidly expanding field of cyber-physical systems with a Long-needed foundational text by an established authority This book is primarily aimed at advanced undergraduates, graduates of computer science. Engineers will also find this book useful.

This book is a collection of research work conducted by researchers at Centre for Smart Grid Energy Research (CSMER), Institute of Autonomous System, Universiti Teknologi PETRONAS (UTP), and Seismic Modelling and Inversion Group, King Abdullah University of Science and Technology (KAUST), Saudi Arabia. The book covers topics in the field of renewable energy where visualization, artificial neural network and deep learning techniques have been applied to optimize the performance of various applications in energy-related industries. These examples include a natural gas vehicle (NGV), a single axis and a fixed axis solar tracker, seismic inversion enhanced oil recovery, viability of a PV system and construction of a septic B-spline tensor product scheme. Readers will benefit from these examples, which describe the current trend of energy optimization techniques in renewable energy applications making it a good reference for the researchers and industrial practitioners working in the field of renewable energy and optimization techniques.

Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring. Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners. This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.

Covers technologies considered to explore, predict, operation and maintenance of renewable energy sources Aids design and use of renewable energy sources including application of artificial intelligence in a real-time environment Includes IoT, Cloud Computing, Big data, Smart Grid and different optimization techniques for resource forecasting, installation, operation, and optimization of energy generation Discusses the principle of integration/hybridization of renewable energy sources along with their optimization based on energy requirement. Reviews concept and challenges involved in the implementation of smart grid.

Focuses on new machine learning developments that can lead to newly developed applications Uses a predictive and futuristic approach which makes Machine Learning a promising tool for business processes and sustainable solutions Promotes newer algorithms which are more efficient and reliable for a new dimension in discovering certain latent domains of applications Discusses the huge potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making Offers many real-time case studies

This text will help readers in gaining knowledge in designing power electronic converters and its control for electric vehicles. It discusses the ways in which power from electric vehicle batteries is transferred to an electric motor, the technology used for charging electric vehicle batteries, and the energy storage. The text covers case studies and real-life examples related to electric vehicles. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, environmental engineering, automotive engineering, and computer science. The book Discusses the latest advances and developments in the field of electric vehicles Covers advanced concepts including grid-to-vehicle power transfer, vehicle-to-vehicle charging, and regenerative braking Examines the challenges associate with the integration of renewable energy sources with electric vehicles Highlights basic understanding of the charging infrastructure for electric vehicles Covers concepts including the reliability of power converters in electric vehicles, and battery management systems This book discusses the challenges, emerging technologies, and recent development of power electronics for electric vehicles. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, environmental engineering, automotive engineering, and computer science.

This book is a collection of research work conducted by researchers at Centre for Smart Grid Energy Research (CSMER), Institute of Autonomous System, Universiti Teknologi PETRONAS (UTP), and Seismic Modelling and Inversion Group, King Abdullah University of Science and Technology (KAUST), Saudi Arabia. The book covers topics in the field of renewable energy where visualization, artificial neural network and deep learning techniques have been applied to optimize the performance of various applications in energy-related industries. These examples include a natural gas vehicle (NGV), a single axis and a fixed axis solar tracker, seismic inversion enhanced oil recovery, viability of a PV system and construction of a septic B-spline tensor product scheme. Readers will benefit from these examples, which describe the current trend of energy optimization techniques in renewable energy applications making it a good reference for the researchers and industrial practitioners working in the field of renewable energy and optimization techniques.

This book presents recent science and engineering research in the field of conventional and renewable energy, energy efficiency and optimization, discussing problems such as availability, peak load and reliability of sustainable supply for power to consumers. Such research is imperative since efficient and environmentally friendly solutions are critical in modern electricity production and transmission.

This book highlights state-of-the-art research on renewable energy integration technology and suitable and efficient power generation, discussing smart grids, renewable energy grid integration, prediction control models, and econometric models for predicting the global solar radiation and factors that affect solar radiation, performance evaluation of photovoltaic systems, and improved energy consumption prediction models. It discusses several methods, algorithms, environmental data-based performance analyses, and experimental results to help readers gain a detailed understanding of the pros and cons of technologies in this rapidly growing area. Accordingly, it offers a valuable resource for students and researchers working on renewable energy optimization models.

Augmented and Virtual Reality are revolutionizing present and future technologies: these are the fastest growing and most fascinating areas of technologies at present. This book aims to provide insight into the theory and applications of Augmented and Virtual Reality to multiple technologies such as IoT (Internet of Things), ML (Machine Learning), AI (Artificial Intelligence), Healthcare and Education.