Rashmi Gupta – författare

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.

This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding.

This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.

This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding.

This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens'' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.

Key sailing Features:

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens'' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations.

Key sailing Features:

This book focuses on the fusion of artificial intelligence and machine learning in advanced image processing, data analysis, and cyber security, as well as compiles and discusses various engineering solutions using various artificial intelligence paradigms. It looks at recent technological advancements and considers how artificial intelligence, machine learning, deep learning, soft computing, and evolutionary computing techniques can be used to design, implement, and optimize advanced image processing, data analysis, and cyber security engineering solutions. It will readers develop the insight required to use the tools of digital imaging to solve new problems.

The book is divided into sections that deal with

Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security offers a selection of chapters on the application of artificial intelligence and machine learning for advanced image processing, data analysis, and cyber security. This book will surely enhance the knowledge of readers interested in these areas.

This book focuses on the fusion of artificial intelligence and machine learning in advanced image processing, data analysis, and cyber security, as well as compiles and discusses various engineering solutions using various artificial intelligence paradigms. It looks at recent technological advancements and considers how artificial intelligence, machine learning, deep learning, soft computing, and evolutionary computing techniques can be used to design, implement, and optimize advanced image processing, data analysis, and cyber security engineering solutions. It will readers develop the insight required to use the tools of digital imaging to solve new problems.

The book is divided into sections that deal with

Fusion of Artificial Intelligence and Machine Learning for Advanced Image Processing, Data Analysis, and Cyber Security offers a selection of chapters on the application of artificial intelligence and machine learning for advanced image processing, data analysis, and cyber security. This book will surely enhance the knowledge of readers interested in these areas.

Ambient assisted living (AAL) utilizes information and communication technology to empower individuals to maintain an active and independent lifestyle for as long as possible. The concept of AAL has been around for decades, but with the evolution of the healthcare sector, we have seen significant advancements in AAL technologies. In recent years, there has been a growing trend towards living alone, and AAL plays a crucial role in supporting individuals to live independently. Ambient Assisted Living (AAL) Technologies: Transitioning from Healthcare 4.0 to Healthcare 5.0 is divided into four comprehensive sections that explore the shift from Healthcare 4.0 to Healthcare 5.0.

It covers AAL technology in the context of Healthcare 4.0 and the Internet of Things (IoT) and fog computing frameworks for real-time applications of natural language processing (NLP) in AAL. The text also delves into advanced artificial intelligence methods for data analytics in AAL, focusing on real-time applications and data analysis for practical use. Additionally, the book covers advanced enabling technologies like blockchain, big data, fog computing and cutting-edge AI techniques for assisted living in Healthcare 5.0. The integration of these technologies and perspectives is crucial for advancing assisted living in the realm of Healthcare 5.0. This book is perfect for students and researchers specializing in AAL and NLP. Professionals working on products for assisted living can also benefit from the valuable insights provided by recent research to improve the efficiency and advancement of their products.

The topic of AAL is already a part of the curriculum in many universities and institutes, and this book will help students explore the various applications of NLP within this field. In addition, individuals looking to engage in innovative projects can find inspiration from the latest advancements in AAL.

Ambient assisted living (AAL) utilizes information and communication technology to empower individuals to maintain an active and independent lifestyle for as long as possible. The concept of AAL has been around for decades, but with the evolution of the healthcare sector, we have seen significant advancements in AAL technologies. In recent years, there has been a growing trend towards living alone, and AAL plays a crucial role in supporting individuals to live independently. Ambient Assisted Living (AAL) Technologies: Transitioning from Healthcare 4.0 to Healthcare 5.0 is divided into four comprehensive sections that explore the shift from Healthcare 4.0 to Healthcare 5.0.

It covers AAL technology in the context of Healthcare 4.0 and the Internet of Things (IoT) and fog computing frameworks for real-time applications of natural language processing (NLP) in AAL. The text also delves into advanced artificial intelligence methods for data analytics in AAL, focusing on real-time applications and data analysis for practical use. Additionally, the book covers advanced enabling technologies like blockchain, big data, fog computing and cutting-edge AI techniques for assisted living in Healthcare 5.0. The integration of these technologies and perspectives is crucial for advancing assisted living in the realm of Healthcare 5.0. This book is perfect for students and researchers specializing in AAL and NLP. Professionals working on products for assisted living can also benefit from the valuable insights provided by recent research to improve the efficiency and advancement of their products.

The topic of AAL is already a part of the curriculum in many universities and institutes, and this book will help students explore the various applications of NLP within this field. In addition, individuals looking to engage in innovative projects can find inspiration from the latest advancements in AAL.

Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of Technology Computer Aided Design (TCAD). It provides the various algorithms of machine learning such as regression, decision tree, support vector machine and k-means clustering and so forth. This book also highlights semiconductor materials and their uses in multi-gate devices, analog and Radio Frequency (RF) behaviour of semiconductor devices with different materials.

Features:

This book is aimed at researchers and graduate students in semiconductor materials, machine learning, and electrical engineering.

Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of Technology Computer Aided Design (TCAD). It provides the various algorithms of machine learning such as regression, decision tree, support vector machine and k-means clustering and so forth. This book also highlights semiconductor materials and their uses in multi-gate devices, analog and Radio Frequency (RF) behaviour of semiconductor devices with different materials.

Features:

This book is aimed at researchers and graduate students in semiconductor materials, machine learning, and electrical engineering.