Anil Kumar Sagar – författare

Artificial Intelligence (AI) and the Internet of Things (IoT) are growing rapidly in today’s business world. In today's era, 25 billion devices, including machines, sensors, and cameras, are connected and continue to grow steadily. It is assumed that in 2025, 41.6 billion IoT devices will be connected, generating around 79.4 zettabytes of data.IoT and AI are intersecting in various scenarios. IoT-enabled devices are generating a huge amount of data, and with the help of AI, this data is used to build various intelligent models. These intelligent models are helpful in our daily lives and make the world smarter.Artificial Intelligence in Cyber Physical Systems: Principles and Applications addresses issues related to system safety, security, reliability, and deployment strategies in healthcare, military, transportation, energy, infrastructure, smart homes, and smart cities.

Artificial Intelligence (AI) and the Internet of Things (IoT) are growing rapidly in today’s business world. In today's era, 25 billion devices, including machines, sensors, and cameras, are connected and continue to grow steadily. It is assumed that in 2025, 41.6 billion IoT devices will be connected, generating around 79.4 zettabytes of data.IoT and AI are intersecting in various scenarios. IoT-enabled devices are generating a huge amount of data, and with the help of AI, this data is used to build various intelligent models. These intelligent models are helpful in our daily lives and make the world smarter.Artificial Intelligence in Cyber Physical Systems: Principles and Applications addresses issues related to system safety, security, reliability, and deployment strategies in healthcare, military, transportation, energy, infrastructure, smart homes, and smart cities.

Intelligent Techniques for Cyber-Physical Systems covers challenges, opportunities, and open research directions for cyber-physical systems (CPS). It focuses on the design and development of machine learning and metaheuristics-enabled methods as well as blockchain for various challenges like security, resource management, computation offloading, trust management, and others in edge, fog, and cloud computing, Internet of Things (IoT), Internet of Everything (IoE), and smart cities. It also includes the design and analysis of deep learning-based models, sensing technologies, metaheuristics, and blockchain for complex real-life systems for CPS.Offers perspectives on the research directions in CPS;Provides state-of-the-art reviews on intelligent techniques, machine learning, deep learning, and reinforcement learning-based models for cloud-enabled IoT environment;Discusses intelligent techniques for complex real-life problems in different CPS scenarios;Reviews advancements in blockchain technology and smart cities;Explores machine learning-based intelligent models for combinatorial optimization problems.The book is aimed at researchers and graduate students in computer science, engineering, and electrical and electronics engineering.

Intelligent Techniques for Cyber-Physical Systems covers challenges, opportunities, and open research directions for cyber-physical systems (CPS). It focuses on the design and development of machine learning and metaheuristics-enabled methods as well as blockchain for various challenges like security, resource management, computation offloading, trust management, and others in edge, fog, and cloud computing, Internet of Things (IoT), Internet of Everything (IoE), and smart cities. It also includes the design and analysis of deep learning-based models, sensing technologies, metaheuristics, and blockchain for complex real-life systems for CPS.Offers perspectives on the research directions in CPS;Provides state-of-the-art reviews on intelligent techniques, machine learning, deep learning, and reinforcement learning-based models for cloud-enabled IoT environment;Discusses intelligent techniques for complex real-life problems in different CPS scenarios;Reviews advancements in blockchain technology and smart cities;Explores machine learning-based intelligent models for combinatorial optimization problems.The book is aimed at researchers and graduate students in computer science, engineering, and electrical and electronics engineering.

The book presents the latest developments in intelligent communication networks based on applicability from various domains of artificial intelligence and machine learning including channel modeling, model-based structure, channel prediction, and signal detection. It further explains important topics such as vehicular mobility modeling, human-centric network applications, security and privacy in social networks, and trust-based intelligent transportation systems. This book:Presents a model-based approach to constructing an effective network by using state-of-the-art artificial intelligent techniques. Discusses the theoretical and practical applications of channel prediction and signal detection. Introduces the fundamental concepts and application of vehicular networks in conjunction with artificial intelligence. Explores wireless communication network techniques enabled by human-centric applications, designed, and developed with artificial intelligence characteristics. Highlights the challenges in designing and developing an effective and intelligent communication network that can be applied in different domains of human activities for finding sustainable solutions.It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer engineering, and information technology.