As the progression of the internet continues, society is finding easier, quicker ways of simplifying their needs with the use of technology. With the growth of lightweight devices, such as smart phones and wearable devices, highly configured hardware is in heightened demand in order to process the large amounts of raw data that are acquired. Connecting these devices to fog computing can reduce bandwidth and latency for data transmission when associated with centralized cloud solutions and uses machine learning algorithms to handle large amounts of raw data. The risks that accompany this advancing technology, however, have yet to be explored. Architecture and Security Issues in Fog Computing Applications is a pivotal reference source that provides vital research on the architectural complications of fog processing and focuses on security and privacy issues in intelligent fog applications. While highlighting topics such as machine learning, cyber-physical systems, and security applications, this publication explores the architecture of intelligent fog applications enabled with machine learning. This book is ideally designed for IT specialists, software developers, security analysts, software engineers, academicians, students, and researchers seeking current research on network security and wireless systems.

Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals.

With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Digital transformation is a revolutionary technology that will play a vital role in major industries, including global governments. These administrations are taking the initiative to incorporate digital programs with their objective being to provide digital infrastructure as a basic utility for every citizen, provide on demand services with superior governance, and empower their citizens digitally. However, security and privacy are major barriers in adopting these mechanisms, as organizations and individuals are concerned about their private and financial data. Impact of Digital Transformation on Security Policies and Standards is an essential research book that examines the policies, standards, and mechanisms for security in all types of digital applications and focuses on blockchain and its imminent impact on financial services in supporting smart government, along with bitcoin and the future of digital payments. Highlighting topics such as cryptography, privacy management, and e-government, this book is ideal for security analysts, data scientists, academicians, policymakers, security professionals, IT professionals, government officials, finance professionals, researchers, and students.

Enterprise Systems have been used for many years to integrate technology with the management of an organization but rapid technological disruptions are now creating new challenges and opportunities that require urgent consideration. This book reappraises the implementation and management of Enterprise Systems in the digital age and investigates the vital link between business processes, information technology and the Internet for an organization's competitive advantage and success. This book primarily focuses on the implementation, operation, management and integration of Enterprise Systems with fastemerging disruptive technologies such as blockchains, big data, cryptocurrencies, artificial intelligence, cloud computing, data mining and data analytics. These disruptive technologies are now becoming mainstream and the book proposes several innovations that organizations need to adopt to remain competitive within this rapidly changing landscape. In addition, it examines Enterprise Systems, their components, architecture, and applications and enlightens readers on the benefits and shortcomings of implementing them. This book contains primary research on organizations, case studies, and benchmarks ERP implementation against international best practice.

This book discusses the convergence of artificial intelligence (AI) and Blockchain and how they can work together to help reach the goals of Industry 4.0. The authors first discuss how AI and Blockchain can help increase performance in business. The authors go on to discuss how the technologies can integrate to provide a competitive edge for businesses through improvements in big data, which has allowed firms to organize huge datasets into structured components that computers can process quickly. The authors also cover security implications and how AI and Blockchain can act as a double-edged sword against cyber-attacks. Impacts in programming, calculations, robotization, robots, and equipment are also discussed. This book caters to an extensive cross-sectional and multi-disciplinary readership. Academics, researchers and their students in topics such as artificial intelligence, cyber-physical systems, ethics, robotics, safety engineering, and safety-critical systems should find the book of value.

This book explores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. This book provides practical and use case oriented approaches for IOT-based agricultural systems. Predictive Analysis in Smart Agriculture deals with all aspects of smart agriculture with state-of-the-art predictive analysis in the complete 360-degree view spectrum. The book includes the concepts of urban and vertical farming using Agro IoT systems and renewable energy sources for modern agriculture trends. It discusses the real-world challenges, complexities in Agro IoT, and advantages of incorporating smart technology. It also presents the rapid advancement of the technologies in the existing Agri model by applying the various techniques. Novel architectural solutions in smart agricultural engineering are the core aspects of this book. Several predictive analysis tools and smart agriculture are also incorporated. This book can be used as a textbook for students in predictive analysis, agriculture engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in cloud computing, IoT, big data, machine learning, and deep learning working on smart agriculture applications.

This book covers the growing convergence between Blockchain and Artificial Intelligence for Big Data, Multi-Agent systems, the Internet of Things and 5G technologies. Using real case studies and project outcomes, it illustrates the intricate details of blockchain in these real-life scenarios. The contributions from this volume bring a state-of-the-art assessment of these rapidly evolving trends in a creative way and provide a key resource for all those involved in the study and practice of AI and Blockchain.

Reviews recent developments in Artificial Intelligence, IoT, and Big data Discusses the keys issues of security, management, and realization of possible solutions to hurdles in sustainable development Provides key characteristics of problems and approaches in the field of IoT, Big data, and Artificial Intelligence with a focus on sustainable development Examines the applications and implementation of Big data IoT, AI strategies to facilitate the sustainable development goals set by the United Nations by 2030 Explores various algorithms and models for various applications such as health care, financial, education, smart cities, smart cars

This book presents chapters from diverse range of authors on different aspects of how Blockchain and IoT are converging and the impacts of these developments. The book provides an extensive cross-sectional and multi-disciplinary look into this trend and how it affects artificial intelligence, cyber-physical systems, and robotics with a look at applications in aerospace, agriculture, automotive, critical infrastructures, healthcare, manufacturing, retail, smart transport systems, smart cities, and smart healthcare. Cases include the impact of Blockchain for IoT Security; decentralized access control systems in IoT; Blockchain architecture for scalable access management in IoT; smart and sustainable IoT applications incorporating Blockchain, and more. The book presents contributions from international academics, researchers, and practitioners from diverse perspectives. Presents how Blockchain and IoT are converging and the impacts of these developments on technology and its application; Discusses IoT and Blockchain from cross-sectional and multi-disciplinary perspectives; Includes contributions from researchers, academics, and professionals from around the world.

Distributed Computing to Blockchain: Architecture, Technology, and Applications provides researchers, computer scientists and data scientists with a comprehensive and applied reference covering the evolution of distributed systems computing into blockchain and associated systems such as consensus algorithms, distributed ledgers, DApps, byzantine fault tolerance, distributed databases and operating systems. Sections cover key concepts and technologies such as distributed systems and their architecture, distributed ledger and decentralized web, application and properties of crypto economics, blockchain crypto-analysis for distributed systems followed by DApps architecture. Other sections cover blockchain architecture and security, including smart contracts, tokens, and more. The authors then review byzantine fault tolerance (BFT), distributed ledgers vs. blockchains, and blockchain protocols. The security issues of blockchain and how it aims to resolve trust problems is also covered, along with consensus algorithms used in blockchain. Throughout the book, the presentation of key concepts is supported by real-world tools, algorithms, programming languages and technology to support the implementation of distributed ledger and blockchain in a variety of fields, including healthcare, finance, legal and business applications.

This book serves as a reference for scholars, researchers and practitioners to update their knowledge on methodologies, theoretical analyses, modeling, simulation and empirical studies on blockchain technologies and cryptocurrencies. Chapters on the evolving theory and practice related to distributed ledger technologies and peer-to-peer digital currencies are intended to provide comprehensive coverage and understanding of their uses within the technological, business, and organizational domains.The contributions from this volume also provide a thorough examination of blockchains and cryptocurrencies with respect to issues of management, governance, trust and privacy, and interoperability.Contributed by a diverse range of authors from both academia and professional fields, this reference book presents frontier research in the fields of blockchains and cryptocurrencies.

This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco. This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation, AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.

This book presents chapters from diverse range of authors on different aspects of how Blockchain and IoT are converging and the impacts of these developments. The book provides an extensive cross-sectional and multi-disciplinary look into this trend and how it affects artificial intelligence, cyber-physical systems, and robotics with a look at applications in aerospace, agriculture, automotive, critical infrastructures, healthcare, manufacturing, retail, smart transport systems, smart cities, and smart healthcare. Cases include the impact of Blockchain for IoT Security; decentralized access control systems in IoT; Blockchain architecture for scalable access management in IoT; smart and sustainable IoT applications incorporating Blockchain, and more. The book presents contributions from international academics, researchers, and practitioners from diverse perspectives. Presents how Blockchain and IoT are converging and the impacts of these developments on technology and its application; Discusses IoT and Blockchain from cross-sectional and multi-disciplinary perspectives; Includes contributions from researchers, academics, and professionals from around the world.

With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Digital transformation is a revolutionary technology that will play a vital role in major industries, including global governments. These administrations are taking the initiative to incorporate digital programs with their objective being to provide digital infrastructure as a basic utility for every citizen, provide on demand services with superior governance, and empower their citizens digitally. However, security and privacy are major barriers in adopting these mechanisms, as organizations and individuals are concerned about their private and financial data. Impact of Digital Transformation on Security Policies and Standards is an essential research book that examines the policies, standards, and mechanisms for security in all types of digital applications and focuses on blockchain and its imminent impact on financial services in supporting smart government, along with bitcoin and the future of digital payments. Highlighting topics such as cryptography, privacy management, and e-government, this book is ideal for security analysts, data scientists, academicians, policymakers, security professionals, IT professionals, government officials, finance professionals, researchers, and students.

Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals.

Enterprise Systems have been used for many years to integrate technology with the management of an organization but rapid technological disruptions are now creating new challenges and opportunities that require urgent consideration. This book reappraises the implementation and management of Enterprise Systems in the digital age and investigates the vital link between business processes, information technology and the Internet for an organization's competitive advantage and success. This book primarily focuses on the implementation, operation, management and integration of Enterprise Systems with fastemerging disruptive technologies such as blockchains, big data, cryptocurrencies, artificial intelligence, cloud computing, data mining and data analytics. These disruptive technologies are now becoming mainstream and the book proposes several innovations that organizations need to adopt to remain competitive within this rapidly changing landscape. In addition, it examines Enterprise Systems, their components, architecture, and applications and enlightens readers on the benefits and shortcomings of implementing them. This book contains primary research on organizations, case studies, and benchmarks ERP implementation against international best practice.

As the progression of the internet continues, society is finding easier, quicker ways of simplifying their needs with the use of technology. With the growth of lightweight devices, such as smart phones and wearable devices, highly configured hardware is in heightened demand in order to process the large amounts of raw data that are acquired. Connecting these devices to fog computing can reduce bandwidth and latency for data transmission when associated with centralized cloud solutions and uses machine learning algorithms to handle large amounts of raw data. The risks that accompany this advancing technology, however, have yet to be explored. Architecture and Security Issues in Fog Computing Applications is a pivotal reference source that provides vital research on the architectural complications of fog processing and focuses on security and privacy issues in intelligent fog applications. While highlighting topics such as machine learning, cyber-physical systems, and security applications, this publication explores the architecture of intelligent fog applications enabled with machine learning. This book is ideally designed for IT specialists, software developers, security analysts, software engineers, academicians, students, and researchers seeking current research on network security and wireless systems.