As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue.

Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.

Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue.

Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.

Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.

Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.

This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.

The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.

Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.

Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.

This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.

The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.

Digital Twins and Cybersecurity delves into the intricacies of digital twins, covering emerging trends in digital twin technology, and understands the complex relationship between digital twins and cybersecurity. This book highlights the growing threats in the digital landscape and cybersecurity measures to ensure the integrity and confidentiality of digital twin ecosystems. With a focus on the significance of cybersecurity, the book outlines the potential consequences of cyber-attacks on digital twins and emphasizes the importance of robust authentication, access control, and proactive threat detection.

The chapters encompass a wide range of topics based on real-world case studies offering valuable insights into digital twin technology, the various types of digital twins, and solutions for future developments. This book also delves into the challenges and mitigation strategies for digital twins in industries such as manufacturing, healthcare, and transportation. In addition to the topics covered in this book, Digital Twins and Cybersecurity aims to bridge the gap between theoretical knowledge and practical implementation. Lastly, this book is accessible to a wide range of readers, including professionals in industries to provide future challenges and developments in this dynamic space.

Digital Twins and Cybersecurity delves into the intricacies of digital twins, covering emerging trends in digital twin technology, and understands the complex relationship between digital twins and cybersecurity. This book highlights the growing threats in the digital landscape and cybersecurity measures to ensure the integrity and confidentiality of digital twin ecosystems. With a focus on the significance of cybersecurity, the book outlines the potential consequences of cyber-attacks on digital twins and emphasizes the importance of robust authentication, access control, and proactive threat detection.

The chapters encompass a wide range of topics based on real-world case studies offering valuable insights into digital twin technology, the various types of digital twins, and solutions for future developments. This book also delves into the challenges and mitigation strategies for digital twins in industries such as manufacturing, healthcare, and transportation. In addition to the topics covered in this book, Digital Twins and Cybersecurity aims to bridge the gap between theoretical knowledge and practical implementation. Lastly, this book is accessible to a wide range of readers, including professionals in industries to provide future challenges and developments in this dynamic space.

This book provides a novel solution for existing challenges in wireless body sensor networks (WBAN) such as network lifetime, fault tolerant approaches, reliability, security, and privacy. The contributors first discuss emerging trends of WBAN in the present health care system. They then provide possible solutions to challenges inherent in WBANs. Finally, they discuss results in working environments. Topics include communication protocols of implanted, wearable and nano body sensor networks; energy harvesting methodologies and experimentation for WBAN; reliability analysis and fault tolerant architecture for WBAN; and handling network failure during critical duration. The contributors consist of researchers and practitioners in WBAN around the world.

This book exploits the benefits of integration of wireless sensor networks (WSN) and Internet of Things (IoT) for smart cities. The authors discuss WSN and IoT in tackling complex computing tasks and challenges in the fields of disaster relief, security, and weather forecasting (among many others). This book highlights the challenges in the field of quality of service metrics (QoS) in the WSN based IoT applications. Topics include IoT Applications for eHealth, smart environments, intelligent transportation systems, delay tolerant models for IoT applications, protocols and architectures for industrial IoT, energy efficient protocols, and much more. Readers will get to know the solutions of these problems for development of smart city applications with the integration of WSN with IoT.

This book discusses advances in smart and sustainable development of smart environments. The authors discuss the challenges faced in developing sustainable smart applications and provide potential solutions. The solutions are aimed at improving reliability and security with the goal of affordability, safety, and durability. Topics include health care applications, sustainable smart transportation systems, intelligent sustainable wearable electronics, and sustainable smart building and alert systems. Authors are from both industry and academia and present research from around the world.

As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue.

Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.

Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue.

Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.

Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.

Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.

This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.

The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.

Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.

Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.

This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.

The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.

Digital Twins and Cybersecurity delves into the intricacies of digital twins, covering emerging trends in digital twin technology, and understands the complex relationship between digital twins and cybersecurity. This book highlights the growing threats in the digital landscape and cybersecurity measures to ensure the integrity and confidentiality of digital twin ecosystems. With a focus on the significance of cybersecurity, the book outlines the potential consequences of cyber-attacks on digital twins and emphasizes the importance of robust authentication, access control, and proactive threat detection.

The chapters encompass a wide range of topics based on real-world case studies offering valuable insights into digital twin technology, the various types of digital twins, and solutions for future developments. This book also delves into the challenges and mitigation strategies for digital twins in industries such as manufacturing, healthcare, and transportation. In addition to the topics covered in this book, Digital Twins and Cybersecurity aims to bridge the gap between theoretical knowledge and practical implementation. Lastly, this book is accessible to a wide range of readers, including professionals in industries to provide future challenges and developments in this dynamic space.

Digital Twins and Cybersecurity delves into the intricacies of digital twins, covering emerging trends in digital twin technology, and understands the complex relationship between digital twins and cybersecurity. This book highlights the growing threats in the digital landscape and cybersecurity measures to ensure the integrity and confidentiality of digital twin ecosystems. With a focus on the significance of cybersecurity, the book outlines the potential consequences of cyber-attacks on digital twins and emphasizes the importance of robust authentication, access control, and proactive threat detection.

The chapters encompass a wide range of topics based on real-world case studies offering valuable insights into digital twin technology, the various types of digital twins, and solutions for future developments. This book also delves into the challenges and mitigation strategies for digital twins in industries such as manufacturing, healthcare, and transportation. In addition to the topics covered in this book, Digital Twins and Cybersecurity aims to bridge the gap between theoretical knowledge and practical implementation. Lastly, this book is accessible to a wide range of readers, including professionals in industries to provide future challenges and developments in this dynamic space.

This book provides a novel solution for existing challenges in wireless body sensor networks (WBAN) such as network lifetime, fault tolerant approaches, reliability, security, and privacy. The contributors first discuss emerging trends of WBAN in the present health care system. They then provide possible solutions to challenges inherent in WBANs. Finally, they discuss results in working environments. Topics include communication protocols of implanted, wearable and nano body sensor networks; energy harvesting methodologies and experimentation for WBAN; reliability analysis and fault tolerant architecture for WBAN; and handling network failure during critical duration. The contributors consist of researchers and practitioners in WBAN around the world.

This book exploits the benefits of integration of wireless sensor networks (WSN) and Internet of Things (IoT) for smart cities. The authors discuss WSN and IoT in tackling complex computing tasks and challenges in the fields of disaster relief, security, and weather forecasting (among many others). This book highlights the challenges in the field of quality of service metrics (QoS) in the WSN based IoT applications. Topics include IoT Applications for eHealth, smart environments, intelligent transportation systems, delay tolerant models for IoT applications, protocols and architectures for industrial IoT, energy efficient protocols, and much more. Readers will get to know the solutions of these problems for development of smart city applications with the integration of WSN with IoT.

This book discusses advances in smart and sustainable development of smart environments. The authors discuss the challenges faced in developing sustainable smart applications and provide potential solutions. The solutions are aimed at improving reliability and security with the goal of affordability, safety, and durability. Topics include health care applications, sustainable smart transportation systems, intelligent sustainable wearable electronics, and sustainable smart building and alert systems. Authors are from both industry and academia and present research from around the world.