Alex Khang – författare

This edited book describes how newly emerging Artificial Intelligence (AI) technologies will provide unprecedented opportunities to penetrate technology and automation into everything we do, and at the same time, provide a huge playing field for businesses to develop newer models to capture market share.

It establishes a milestone in understanding global transformational changes occurring in the manufacturing and corporate world due to AI and tries to find powerful and sophisticated solutions that will improve and streamline operations.

Reinventing Manufacturing and Business Processes Through Artificial Intelligence will be of interest to students, researchers, and professionals of the AI community as well as interdisciplinary researchers.

This edited book describes how newly emerging Artificial Intelligence (AI) technologies will provide unprecedented opportunities to penetrate technology and automation into everything we do, and at the same time, provide a huge playing field for businesses to develop newer models to capture market share.

It establishes a milestone in understanding global transformational changes occurring in the manufacturing and corporate world due to AI and tries to find powerful and sophisticated solutions that will improve and streamline operations.

Reinventing Manufacturing and Business Processes Through Artificial Intelligence will be of interest to students, researchers, and professionals of the AI community as well as interdisciplinary researchers.

Today, relevant data are typically delivered to cloud-based servers for storing and analysis in order to extract key features and enable enhanced applications beyond the basic transmission of raw data and to realize the possibilities associated with the impending Internet of Things (IoT). To allow for quicker, more efficient, and expanded privacy-preserving services, a new trend called Fog Computing has emerged: moving these responsibilities to the network''s edge.

Traditional centralized cloud computing paradigms confront new problems posed by IoT application growth, including high latency, limited storage, and outages due to a lack of available resources. Fog Computing puts the cloud and IoT devices closer together to address these issues. Instead of sending IoT data to the cloud, the fog processes and stores it locally at IoT devices. Unlike the cloud, fog-based services have a faster reaction time and better quality overall.

Fog Computing, Cloud Computing, and their connectivity with the IoT are discussed in this book, with an emphasis on the advantages and implementation issues. It also explores the various architectures and appropriate IoT applications. Fog Computing, Cloud Computing, and Internet of Things are being suggested as potential research directions.

Features:

Today, relevant data are typically delivered to cloud-based servers for storing and analysis in order to extract key features and enable enhanced applications beyond the basic transmission of raw data and to realize the possibilities associated with the impending Internet of Things (IoT). To allow for quicker, more efficient, and expanded privacy-preserving services, a new trend called Fog Computing has emerged: moving these responsibilities to the network''s edge.

Traditional centralized cloud computing paradigms confront new problems posed by IoT application growth, including high latency, limited storage, and outages due to a lack of available resources. Fog Computing puts the cloud and IoT devices closer together to address these issues. Instead of sending IoT data to the cloud, the fog processes and stores it locally at IoT devices. Unlike the cloud, fog-based services have a faster reaction time and better quality overall.

Fog Computing, Cloud Computing, and their connectivity with the IoT are discussed in this book, with an emphasis on the advantages and implementation issues. It also explores the various architectures and appropriate IoT applications. Fog Computing, Cloud Computing, and Internet of Things are being suggested as potential research directions.

Features:

Over the next few years, smart city technologies will be rolled out, and the IoT devices and AI-centric systems will provide even more far-reaching connectivity. This book presents various concepts in the design and development of a smart city and methodologies and solutions involved in designing contemporary infrastructure for building smart cities around the world. The book will focus mainly on six areas of smart city infrastructures: smart city entities, IoT-based solutions, AI-centric control systems, smart systems, cybersecurity mechanisms, data science, and cloud computing for the deployment of the smart ecosystem.

AI-Centric Smart City Ecosystem: Technologies, Design, and Implementation will discuss the role of AI-centric innovative systems and beyond intelligent solutions in the smart city framework. Readers will discover how to apply design principles and technologies for operating intelligent cities and develop an understanding of how to integrate AI-based control systems to make systems smarter. The book will present various concepts in the design and development of smart cities and methodologies and solutions involved in designing modern infrastructure. Also, readers can discover how to develop applications and connect the IoT devices for collecting and mining real-time data and uncover the challenges and techniques for improving the automatic operation in the smart city by using high-tech solutions.

This book is intended to serve the needs of the industry, engineers, professionals, researchers, and master’s and doctoral students studying emerging technologies in smart city ecosystems.

Over the next few years, smart city technologies will be rolled out, and the IoT devices and AI-centric systems will provide even more far-reaching connectivity. This book presents various concepts in the design and development of a smart city and methodologies and solutions involved in designing contemporary infrastructure for building smart cities around the world. The book will focus mainly on six areas of smart city infrastructures: smart city entities, IoT-based solutions, AI-centric control systems, smart systems, cybersecurity mechanisms, data science, and cloud computing for the deployment of the smart ecosystem.

AI-Centric Smart City Ecosystem: Technologies, Design, and Implementation will discuss the role of AI-centric innovative systems and beyond intelligent solutions in the smart city framework. Readers will discover how to apply design principles and technologies for operating intelligent cities and develop an understanding of how to integrate AI-based control systems to make systems smarter. The book will present various concepts in the design and development of smart cities and methodologies and solutions involved in designing modern infrastructure. Also, readers can discover how to develop applications and connect the IoT devices for collecting and mining real-time data and uncover the challenges and techniques for improving the automatic operation in the smart city by using high-tech solutions.

This book is intended to serve the needs of the industry, engineers, professionals, researchers, and master’s and doctoral students studying emerging technologies in smart city ecosystems.

This book focuses on futuristic approaches and designs for real-time systems and applications, as well as the fundamental concepts of including advanced techniques and tools in models of data-driven blockchain ecosystems.

The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies discusses how to implement and manage processes for releasing and delivering blockchain applications. It presents the core of blockchain technology, IoT-based and AI-based blockchain systems, and various manufacturing areas related to Industry 4.0. The book illustrates how to apply design principles to develop and manage blockchain networks, and also covers the role that cloud computing plays in blockchain applications.

All major technologies involved in blockchain-embedded applications are included in this book, which makes it useful to engineering students, researchers, academicians, and professionals interested in the core of blockchain technology.

This book focuses on futuristic approaches and designs for real-time systems and applications, as well as the fundamental concepts of including advanced techniques and tools in models of data-driven blockchain ecosystems.

The Data-Driven Blockchain Ecosystem: Fundamentals, Applications, and Emerging Technologies discusses how to implement and manage processes for releasing and delivering blockchain applications. It presents the core of blockchain technology, IoT-based and AI-based blockchain systems, and various manufacturing areas related to Industry 4.0. The book illustrates how to apply design principles to develop and manage blockchain networks, and also covers the role that cloud computing plays in blockchain applications.

All major technologies involved in blockchain-embedded applications are included in this book, which makes it useful to engineering students, researchers, academicians, and professionals interested in the core of blockchain technology.

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world''s largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues.

Features:

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world''s largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues.

Features:

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem.

Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare.

This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

The book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem.

Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare.

This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

This book discusses the basic principles of sustainable development in a smart city ecosystem to better serve the life of citizens. It examines smart city systems driven by emerging IoT-powered technologies and the other dependent platforms.

Smart Cities: AI, IoT Technologies, Big Data Solutions, Cloud Platforms, and Cybersecurity Techniques discusses the design and implementation of the core components of the smart city ecosystem. The editors discuss the effective management and development of smart city infrastructures, starting with planning and integrating complex models and diverse frameworks into an ecosystem. Specifically the chapters examine the core infrastructure elements, including activities of the public and private services as well as innovative ICT solutions, computer vision, IoT technologies, data tools, cloud services, AR/VR technologies, cybersecurity techniques, treatment solution of the environmental water pollution, and other intelligent devices for supporting sustainable living in the smart environment.

The chapters also discuss machine vision models and implementation as well as real-time robotic applications. Upon reading the book, users will be able to handle the challenges and improvements of security for smart systems, and will have the know-how to analyze and visualize data using big data tools and visualization applications. The book will provide the technologies, solutions as well as designs of smart cities with advanced tools and techniques for students, researchers, engineers, and academics.

This book discusses the basic principles of sustainable development in a smart city ecosystem to better serve the life of citizens. It examines smart city systems driven by emerging IoT-powered technologies and the other dependent platforms.

Smart Cities: AI, IoT Technologies, Big Data Solutions, Cloud Platforms, and Cybersecurity Techniques discusses the design and implementation of the core components of the smart city ecosystem. The editors discuss the effective management and development of smart city infrastructures, starting with planning and integrating complex models and diverse frameworks into an ecosystem. Specifically the chapters examine the core infrastructure elements, including activities of the public and private services as well as innovative ICT solutions, computer vision, IoT technologies, data tools, cloud services, AR/VR technologies, cybersecurity techniques, treatment solution of the environmental water pollution, and other intelligent devices for supporting sustainable living in the smart environment.

The chapters also discuss machine vision models and implementation as well as real-time robotic applications. Upon reading the book, users will be able to handle the challenges and improvements of security for smart systems, and will have the know-how to analyze and visualize data using big data tools and visualization applications. The book will provide the technologies, solutions as well as designs of smart cities with advanced tools and techniques for students, researchers, engineers, and academics.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0.

AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries.

This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0.

AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries.

This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields.

This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools.

This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.

This book covers the need for Internet of Things (IoT) technologies and artificial intelligence (AI)–aided IoT solutions for business and production. It shows how IoT-based technology uses algorithms and AI models to bring out the desired results. AI-Aided IoT Technologies and Applications for Smart Business and Production shows how a variety of IoT technologies can be used toward integrating data fabric solutions and how intelligent applications can be used to greater effect in business and production operations. The book also covers the integration of IoT data-driven financial technology (fintech) applications to fulfill the goals of trusted AI-aided IoT solutions. Next, the authors show how IoT-based technology uses algorithms and AI models to bring out the desired results across various industries including smart cities, buildings, hospitals, hotels, homes, factories, agriculture, transportation, and more. The last part focuses on AI-aided IoT techniques, data analytics, and visualization tools.

This book targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, and professionals. It will be useful to engineering officers, IoT and AI engineers, engineering and industrial management students, and research scholars looking for new ideas, methodologies, technologies, models, frameworks, theories, and practices to resolve the challenging issues associated with leveraging IoT technologies, data-driven analytics, AI-aided models, IoT cybersecurity, 5G, sensors, and augmented and virtual reality techniques for developing smart systems in the era of Industrial Revolution 4.0.

The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market. Within this book, the reader will learn how to implement IoT devices, IoT-equipped machines, and AI-equipped IoT applications using models and methodologies along with an array of case studies.

Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy covers the basics of IoT-equipped machines in developing and managing various activities in many industries. It discusses all of the key points of an AI-enabled IoT solution, which includes predictive analytics, robotic process automation, predictive maintenance, automated processes, IoT technologies and IoT-equipped sensors related to machines and processes, production testing systems, and product assessment processes in the production environment. The book presents the concepts and interactive methods using datasets, processing workflow charts, and architectural diagrams along with additional real-time systems for easy and fast understanding of the application of IoT-equipped machines and AI-enabled solutions in organizations and includes many case studies throughout the book to enforce reader comprehension.

This book is an ideal read for industry specialists, practitioners, researchers, scientists, and engineers working or involved in the fields of Robotics, IT, Computer Science, Soft Computing, IoT, AL/ML/DL, Data Science, the Semantic Web, Knowledge Engineering, and other related fields.

The application of internet of things (IoT) technologies and artificial intelligence (AI)-enabled IoT solutions has gradually become accepted by business and production organizations as an effective tool for automating several activities effectively and efficiently and developing and distributing products to the global market. Within this book, the reader will learn how to implement IoT devices, IoT-equipped machines, and AI-equipped IoT applications using models and methodologies along with an array of case studies.

Advanced IoT Technologies and Applications in the Industry 4.0 Digital Economy covers the basics of IoT-equipped machines in developing and managing various activities in many industries. It discusses all of the key points of an AI-enabled IoT solution, which includes predictive analytics, robotic process automation, predictive maintenance, automated processes, IoT technologies and IoT-equipped sensors related to machines and processes, production testing systems, and product assessment processes in the production environment. The book presents the concepts and interactive methods using datasets, processing workflow charts, and architectural diagrams along with additional real-time systems for easy and fast understanding of the application of IoT-equipped machines and AI-enabled solutions in organizations and includes many case studies throughout the book to enforce reader comprehension.

This book is an ideal read for industry specialists, practitioners, researchers, scientists, and engineers working or involved in the fields of Robotics, IT, Computer Science, Soft Computing, IoT, AL/ML/DL, Data Science, the Semantic Web, Knowledge Engineering, and other related fields.