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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.
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.
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.
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
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 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.
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Sam Goundar
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R3,245
Discovery Miles 32 450
Save R228 (7%)
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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.
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 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.
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.
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.
|
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