In today's digital world, the words "smart" and intelligent" are now used to label devices, machinery, systems, and even environments. What is a "smart" system? Is "smart" synonymous to "intelligent"? If not, what does an "intelligent system" mean? Are all the smart systems intelligent? This book tries to answer these questions through summarizing existing research in various areas and providing new research findings. This book presents new areas of smart and intelligent system design. It defines smart and intelligent systems, offers a human factors approach, discusses networking applications, and combines the human element with smart and intelligent systems. This book is perfect for engineering students in data sciences, artificial intelligence, practitioners at all levels in the field of human factors and ergonomics, systems engineering, computer science, software engineering and robotics.

"The more we know about smart and intelligent systems and their use, the more productive organizations can become, and the more quality of life will improve."—Gavriel Salvendy, President Academy of Science, Engineering and Medicine of Florida, University Distinguished Professor University of Central Florida" "Robots, drones, self-driving cars, and personal assistants are only some of the ‘intelligent’ and ‘smart’ systems which are populating our world and changing the way we use technology to carry out our everyday activities, bringing about both exciting opportunities for human-technology symbiosis, as well as compelling design and development challenges. Through a carefully selected choice of chapters, authored by top scientists in the field, this book, edited by Abbas Moallem, sheds light on fundamental aspects of intelligent and smart systems, investigating the role and impact of affective and psychophysiological computing, machine learning, cybersecurity, agent transparency, and human-agent teaming in the shaping of this new interaction paradigm, as well as the human factors involved in their application in critical domains such as health, education, and manufacturing in the emerging technological landscape."—Constantine Stephanidis, Professor of Computer Science, University of Crete, Distinguished member of Foundation for Research and Technology - Hellas (FORTH) In today’s digital world, the words "smart" and intelligent" are now used to label devices, machinery, systems, and even environments. What is a "smart" system? Is "smart" synonymous with "intelligent"? If not, what does an "intelligent system" mean? Are all smart systems intelligent? This book tries to answer these questions by summarizing the existing research in various areas and providing new research findings. Smart and Intelligent Systems: The Human Elements in Artificial Intelligence, Robotics, and Cybersecurity presents new areas of smart and intelligent system design. It defines smart and intelligent systems, offers a human factors approach, discusses networking applications, and combines the human element with smart and intelligent systems. This book is perfect for engineering students in data sciences and artificial intelligence and practitioners at all levels in the fields of human factors and ergonomics, systems engineering, computer science, software engineering, and robotics.

This book explores the latest research trends in intelligent systems and smart applications. It presents high-quality empirical and review studies focusing on various topics, including information systems and software engineering, knowledge management, technology in education, emerging technologies, and social networks. It provides insights into the theoretical and practical aspects of intelligent systems and smart applications.

From artificial neural net / game theory / semantic applications, to modeling tools, smart manufacturing systems, and data science research – this book offers a broad overview of modern intelligent methods and applications of machine learning, evolutionary computation, Industry 4.0 technologies, and autonomous agents leading to the Internet of Things and potentially a new technological revolution. Though chiefly intended for IT professionals, it will also help a broad range of users of future emerging technologies adapt to the new smart / intelligent wave. In separate chapters, the book highlights fourteen successful examples of recent advances in the rapidly evolving area of intelligent systems. Covering major European projects paving the way to a serious smart / intelligent collaboration, the chapters explore e.g. cyber-security issues, 3D digitization, aerial robots, and SMEs that have introduced cyber-physical production systems. Taken together, they offer unique insights into contemporary artificial intelligence and its potential for innovation.

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

This book highlights the connections between two technologies: artificial intelligence (AI) and Internet of things (IoT). It presents the application of these two technologies to solve various societal problems related to healthcare, agriculture, green environment, renewable energies, smart cities, etc. Each chapter in this book presents novel solutions to these problems along with the challenges in the application of AI and IoT to solve them. It discusses the adverse attacks on machine Learning models and how to protect sensitive data over the IoT networks. It also includes the security issues in IoT and their possible solutions.

Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system’s stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating. Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.