Sita Rani – författare

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.

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 focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.

This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

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.

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.

The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency.

A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.

The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency.

A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.