Explores the potential for disruptive technologies in different industries Addresses the challenges associated with the practical implementation or adoption of disruptive technologies Discusses topics related to IoT, Machine Learning, Sensors, Artificial Intelligence and Cloud Computing for Industry 4.0 and 5.0 Includes examples of the implementation of Industry 4.0 and 5.0 in various sectors, including engineering Contains many case studies for easy comprehension.

As technology continues to advance and the interconnection of various devices makes our lives easier, it also puts us at further risk of privacy and security threats. Phones can connect to household devices to help set alarms, turn on or off the lights, and even preheat ovens. The Internet of Things (IoT) is this symbiotic interplay of smart devices that collect data and make intelligent decisions. However, the lack of an intrinsic security measure within IoT makes it especially vulnerable to privacy and security threats. Blockchain and IoT Integration highlights how Blockchain, an encrypted, distributed computer filing system, can be used to help protect IoT against such privacy and security breaches. The merger of IoT and blockchain technology is a step towards creating a verifiable, secure, and permanent method of recording data processed by "smart" machines. The text explores the platforms and applications of blockchain-enabled IoT as well as helps clarify how to strengthen the IoT security found in healthcare systems as well as private homes. Other highlights of the book include: Overview of the blockchain architecture Blockchain to secure IoT data Blockchain to secure drug supply chain and combat counterfeits Blockchain IoT concepts for smart grids, smart cities, and smart homes A biometric-based blockchain enabled payment system IoT for smart healthcare monitoring systems

With the rapid growth of wireless communications, this book meets the strong demand for information and new research in the area of antenna, signal processing, and microelectronics engineering. Providing an interdisciplinary platform, it brings together leading academicians, scientists, and researchers to share information on innovations, trends, and advances as well as the challenges encountered in this field. The chapters address the functional framework in the area of antenna, signal processing, and microelectronics engineering and explore the concepts from the basic to advanced level. Key features: * Addresses the functional framework in the area of antenna, signal processing, and microelectronics engineering * Covers the major challenges, issues, and advances in antennas, signal processing, and microelectronics engineering * Explores optimization techniques for smart antenna and microelectronics for different applications * Explores different materials and design techniques in the area of antennas and microelectronics

Nanoelectronic Devices for Hardware and Software Security has comprehensive coverage of the principles, basic concepts, structure, modeling, practices, and circuit applications of nanoelectronics in hardware/software security. It also covers the future research directions in this domain. In this evolving era, nanotechnology is converting semiconductor devices dimensions from micron technology to nanotechnology. Nanoelectronics would be the key enabler for innovation in nanoscale devices, circuits, and systems. The motive for this research book is to provide relevant theoretical frameworks that include device physics, modeling, circuit design, and the latest developments in experimental fabrication in the field of nanotechnology for hardware/software security. There are numerous challenges in the development of models for nanoscale devices (e.g., FinFET, gate-all-around devices, TFET, etc.), short channel effects, fringing effects, high leakage current, and power dissipation, among others. This book will help to identify areas where there are challenges and apply nanodevice and circuit techniques to address hardware/software security issues.

This book provides an integrated solution for security and safety in the home, covering both assistance in health monitoring and safety from strangers/intruders who want to enter the home with harmful intentions. It defines a system whereby recognition of a person/stranger at the door is done using three modules: Face Recognition, Voice Recognition and Similarity Index. These three modules are taken together to provide a percentage likelihood that the individual is in the "known" or "unknown" category. The system can also continuously monitor the health parameters of a vulnerable person living alone at home and aid them in calling for help in an emergency. The authors have analyzed a number of existing biometric techniques to provide security for an individual living alone at home. These biometric techniques have been tested using MATLAB (R) image processing and signal processing toolboxes, and results have been calculated on the basis of recognition rate. A major contribution in providing security is a hybrid algorithm proposed by the author named PICA, which combines features of both PCA (Principle Component Analysis) and ICA (Independent Component Analysis) algorithms. This hybrid approach gives better performance recognition than either system alone. The second proposed hybrid algorithm for voice recognition is named as a MFRASTA algorithm by combining features of MFCC (Mel Frequency Cepstral Coefficient) and RASTA-PLP (RelAtive SpecTrA-Perceptual Linear Prediction) algorithm. After performing experiments, results are collected on the basis of recognition rate. The authors have also proposed a third technique named as a Similarity Index to provide trust-based security for an individual. This technique is text independent in which a person is recognized by pronunciation, frequency, tone, pitch, etc., irrespective of the content spoken by the person. By combining these three techniques, a high recognition rate is provided to the person at the door and high security to the individual living independently at home. In the final contribution, the authors have proposed a fingertip-based application for health monitoring by using the concept of sensors. This application is developed using iPhone 6's camera. When a person puts their fingertip on a camera lens, with the help of brightness of the skin, the person's heartbeat will be monitored. This is possible even with a low-quality camera. In case of any emergency, text messages will be sent to the family members of the individual living alone by using 3G Dongle and MATLAB tool. Results show that the proposed work outperforms all the existing techniques used in face recognition, voice recognition, and health monitoring alone.

Provides knowledge on decision making for newly evolving microgrids Discusses techniques on how to improve the quality of power networks by reducing load shedding, power imbalances, and differences between supply and demand during peak hours Offers a collection of knowledge on new techniques for microgrid design Presents emerging fields that now play an important role in microgrid design such as, data science, machine learning, AI, and IT The first book to cover the new trend in the power infrastructure and include areas such as computer science, electrical engineering, electronics engineering and energy engineering

Provides fundamentals of electromagnetism and its applications in a single volume. Covers recent developments in computing and artificial intelligence. Discussion digital signal processing and wireless communication in depth. Covers advanced applications of electromagnetism in communication, spectroscopy, and computing. Discusses Computer Modelling & Simulation, Artificial Intelligence, and Quantum Computing.

This reference text introduces latest mathematical modeling techniques and analysis for renewable energy systems. It comprehensively covers important topics including study of combustion characteristics of laser ignited gasoline-air mixture, hierarchical demand response controller, mathematical modeling of an EOQ for a multi-item inventory system, and integration and modeling of small-scale pumped storage with micro optimization model (HOMER). Aimed at graduate students and academic researchers in the fields of electrical engineering, environmental engineering, mechanical engineering, and civil engineering, this text: Discusses applied mathematical modeling techniques in renewable energy. Covers effective storage and generation of power through renewable energy generation sources. Provides real life applications and problems based on renewable energy. Covers new ways of applying mathematical techniques for applications in diverse areas of science and engineering.

covers advanced subjects in electric machines, starting from principles, to applications and case studies with ample graphical (numerical) results includes notable recent knowledge with strong industrialization potential, such as orthogonal models of multiphase A.C. machines, thermal Finite Element Analysis of (FEA) electric machines, FEA-based-only optimal design of a PM motor case study includes case studies and numerical examples throughout the book includes numerous computer simulation programs in MATLAB and Simulink (R)

This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it's forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It's All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses ....... The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture - the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on 'establishing a center of excellence in analytics'. Simply, "culture - company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses ..... Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses .... Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.

Covers evolutionary approaches to solve optimization problems in biomedical engineering. Discusses IoT, Cloud computing, data analytics in healthcare informatics. Provides computational intelligence-based solution for diagnosis of diseases. Reviews modelling and simulations in designing of biomedical equipment. Promotes machine learning based approaches to improvements in biomedical engineering problems.

This title covers the fundamentals of carbon nanomaterials in a logical and clear manner to make concepts accessible to researchers from different disciplines. It summarizes in a comprehensive manner recent technological and scientific accomplishments in the area of carbon nanomaterials and their application in lithium ion batteries The book also addresses all the components anodes, cathodes and electrolytes of lithium ion battery and discusses the technology of lithium ion batteries that can safely operate at high temperature.

This work is dedicated to CMOS based imaging with the emphasis on the noise modeling, characterization and optimization in order to contribute to the design of high performance imagers in general and range imagers in particular. CMOS is known to be superior to CCD due to its flexibility in terms of integration capabilities, but typically has to be enhanced to compete at parameters as for instance noise, dynamic range or spectral response. Temporal noise is an important topic, since it is one of the most crucial parameters that ultimately limits the performance and cannot be corrected. This work gathers the widespread theory on noise and extends the theory by a non-rigorous but potentially computing efficient algorithm to estimate noise in time sampled systems. This work contributed to two generations of LDPD based ToF range image sensors and proposed a new approach to implement the MSI PM ToF principle. This was verified to yield a significantly faster charge transfer, better linearity, dark current and matching performance. A non-linear and time-variant model is provided that takes into account undesired phenomena such as finite charge transfer speed and a parasitic sensitivity to light when the shutters should remain OFF, to allow for investigations of largesignal characteristics, sensitivity and precision. It was demonstrated that the model converges to a standard photodetector model and properly resembles the measurements. Finally the impact of these undesired phenomena on the range measurement performance is demonstrated.

It is becoming increasingly important to design and develop adaptive, robust, scalable, reliable, security and privacy mechanisms for IoT applications and for Industry 4.0 related concerns. This book serves as a useful guide for researchers and industry professionals and will help beginners to learn the basics to the more advanced topics. Along with exploring security and privacy issues through the IoT ecosystem and examining its implications to the real-world, this book addresses cryptographic tools and techniques and presents the basic and high-level concepts that can serve as guidance for those in the industry as well as help beginners get a handle on both the basic and advanced aspects of security related issues. The book goes on to cover major challenges, issues, and advances in IoT and discusses data processing as well as applications for solutions, and assists in developing self-adaptive cyberphysical security systems that will help with issues brought about by new technologies within IoT and Industry 4.0. This edited book discusses the evolution of IoT and Industry 4.0 and brings security and privacy related technological tools and techniques onto a single platform so that researchers, industry professionals, graduate, postgraduate students, and academicians can easily understand the security, privacy, challenges and opportunity concepts and make then ready to use for applications in IoT and Industry 4.0.

The threat landscape is evolving with tremendous speed. We are facing an extremely fast-growing attack surface with a diversity of attack vectors, a clear asymmetry between attackers and defenders, billions of connected IoT devices, mostly reactive detection and mitigation approaches, and finally big data challenges. The clear asymmetry of attacks and the enormous amount of data are additional arguments to make it necessary to rethink cybersecurity approaches in terms of reducing the attack surface, to make the attack surface dynamic, to automate the detection, risk assessment, and mitigation, and to investigate the prediction and prevention of attacks with the utilization of emerging technologies like blockchain, artificial intelligence and machine learning. This book contains eleven chapters dealing with different Cybersecurity Issues in Emerging Technologies. The issues that are discussed and analyzed include smart connected cars, unmanned ships, 5G/6G connectivity, blockchain, agile incident response, hardware assisted security, ransomware attacks, hybrid threats and cyber skills gap. Both theoretical analysis and experimental evaluation of state-of-the-art techniques are presented and discussed. Prospective readers can be benefitted in understanding the future implications of novel technologies and proposed security solutions and techniques. Graduate and postgraduate students, research scholars, academics, cybersecurity professionals, and business leaders will find this book useful, which is planned to enlighten both beginners and experienced readers.

This volume elaborates on mechatronics as the synergistic integration of mechanical engineering with electronics and intelligent computer control in the design and manufacturing of industrial products and processes. It considers the integration of mechanical systems (mechanical elements, components, machines), electronic systems (microelectronics, sensor and actuator technology), and information technology. The book's chapters present the principles of mechatronic systems design and solid materials in small elementary steps, provide an abundance of examples, and feature problems that are as practical as possible without becoming too involved with many extraneous details.

Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry. This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system. This book is written for Researchers, Students, Professionals, Executives, and the general public.

This book introduces unmanned aircraft systems traffic management (UTM) and how this new paradigm in traffic management integrates unmanned aircraft operations into national airspace systems. Exploring how UTM is expected to operate, including possible architectures for UTM implementations, and UTM services, including flight planning, strategic coordination, and conformance monitoring, Unmanned Aircraft Systems Traffic Management: UTM considers the boundaries of UTM and how it is expected to interlace with tactical coordination systems to maintain airspace safety. The book also presents the work of the global ecosystem of players advancing UTM, including relevant standards development organizations (SDOs), and considers UTM governance paradigms and challenges. FEATURES Describes UTM concept of operations (ConOps) and global variations in architectures Explores envisioned UTM services, including flight planning, strategic coordination, conformance monitoring, contingency management, constraints and geo-awareness, and remote identification Highlights cybersecurity standards development and awareness Covers approaches to the approval, management, and oversight of UTM components and ecosystem Considers the future of UTM and potential barriers to its success, international coordination, and regulatory reform This book is an essential, in-depth, annotated resource for developers, unmanned aircraft system operators, pilots, policy makers, researchers, and academics engaged in unmanned systems, transportation management, and the future of aviation.

This book presents analysis and design for a class of stochastic systems with semi-Markovian jump parameters. It explores systematic analysis of semi-Markovian jump systems via sliding mode control strategy which makes up the shortages in the analysis and design of stochastic systems. This text provides a novel estimation method to deal with the stochastic stability of semi-Markovian jump systems along with design of novel integral sliding surface. Finally, Takagi-Sugeno fuzzy model approach is brought to deal with system nonlinearities and fuzzy sliding mode control laws are provided to ensure the stabilization purpose. Features: Presents systematic work on sliding mode control (SMC) of semi-Markvoain jump systems. Explores SMC methods, such as fuzzy SMC, adaptive SMC, with the presence of generally uncertain transition rates. Provides novel method in dealing with stochastic systems with unknown switching information. Proposes more general theories for semi-Markovian jump systems with generally uncertain transition rates. Discusses practical examples to verify the effectiveness of SMC theory in semi-Markovian jump systems. This book aims at graduate and postgraduate students and for researchers in all engineering disciplines, including mechanical engineering, electrical engineering and applied mathematics, control engineering, signal processing, process control, control theory and robotics.

In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks. In each chapter, the analysis problems are firstly considered, where the stability, synchronization and other performances (e.g., robustness, disturbances attenuation level) are investigated within a unified theoretical framework. In this stage, some novel notions are put forward to reflect the engineering practice. Then, the estimator design issues are discussed where sufficient conditions are derived to ensure the existence of the desired estimators with guaranteed performances. Finally, the theories and techniques developed in previous parts are applied to deal with some issues in several emerging research areas. The book Unifies existing and emerging concepts concerning delayed discrete memristive neural networks with an emphasis on a variety of network-induced phenomena Captures recent advances of theories, techniques, and applications of delayed discrete memristive neural networks from a network-oriented perspective Provides a series of latest results in two popular yet interrelated areas, stability analysis and state estimation of neural networks Exploits a unified framework for analysis and synthesis by designing new tools and techniques in combination with conventional theories of systems science, control engineering and signal processing Gives simulation examples in each chapter to reflect the engineering practice

This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include statistical timing and crosstalk analysis, statistical and parallel analysis, performance bound analysis and behavioral modeling for analog integrated circuits . Among the recent advances, the Binary Decision Diagram (BDD) based approaches are studied in depth. The BDD-based hierarchical symbolic analysis approaches, have essentially broken the analog circuit size barrier.
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This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.

In modern conditions of the development of intelligent systems to solve the problems of smart cities, more and more attention is paid to the construction of distributed intelligent systems, which, based on a network of sensors and specialized calculators, help residents and visitors of the city in real time to solve a whole range of complex problems that arise in an urban environment. In a smart city, much attention is paid to the processing of biometric information that comes from biometric sensors distributed throughout the city. Such biometric systems are multimodal and allow you to control the general condition of a person, and also help a person to move around the city and predict events within the city. This book describes methods for processing biometric information in a smart city environment. The theoretical foundations of building a biometric multisensor network, which allows you to create a unified urban biometric community, are considered. The theoretical foundations of the parallel shift technology and the Radon transformation on cellular automata with a hexagonal covering are presented. On the basis of these technologies, methods of biometric identification by gait parameters and the geometric shape of the auricle are described, which are effectively used in a smart city. A method for tracking dynamic changes in the state of a smart city in real time is considered. Models of behavior of colonies of living organisms, their formation, movement and interaction are described on the basis of the technology of cellular automata with active cells. Models of behavior of active cells in meeting with unwanted cells and models of combining and destruction of active cell colonies are also described. This book is intended for undergraduate, graduate students and specialists working and conducting research in the field of biometric information processing, as well as in the development and construction of distributed intelligent systems.

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.