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This new volume, Cognitive Computing Systems: Applications and
Technological Advancements, explores the emerging area of
artificial intelligence that encompasses machine self-learning,
human-computer interaction, natural language processing, data
mining and more. It introduces cognitive computing systems,
highlights their key applications, discusses the technologies used
in cognitive systems, and explains underlying models and
architectures. Focusing on scientific work for real-world
applications, each chapter presents the use of cognitive computing
and machine learning in specific application areas. These include
the use of speech recognition technology, application of neural
networks in construction management, elevating competency in
education, comprehensive health monitoring systems, predicting type
2 diabetes, applications for smart agricultural technology, human
resource management, and more. With chapters from knowledgeable
researchers in the area of artificial intelligence, cognitive
computing, and allied areas, this book will be an asset for
researchers, faculty, advances students, and industry professionals
in many fields.
This new volume explores a plethora of blockchain-based solutions
for big data and IoT applications, looking at advances in
real-world applications in several sectors, including higher
education, cybersecurity, agriculture, business and management,
healthcare and biomedical science, construction and project
management, smart city development, and others. Chapters explore
emerging technology to combat the ever-increasing threat of
security to computer systems and offer new architectural solutions
for problems encountered in data management and security. The
chapters help to provide a high level of understanding of various
blockchain algorithms along with the necessary tools and
techniques. The novel architectural solutions in the deployment of
blockchain presented here are the core of the book.
This edited book presents an insight for modelling, procuring, and
building the smart city plan using IoT and a security framework
using blockchain technology. The applications of Li-Fi and 5G in
smart cities are included along with their implementation,
challenges, and advantages. This book focusses on use of IoT and
blockchain in day-to-day transparent and recorded activities of
citizens of smart city like smart citizen management. The future
for upgrading the system as per technological advancements is also
discussed. Integrates IoT, blockchain, Li-Fi and 5G in smart city
implementation Covers smart supply chain management using IoT
Outlines the state-of-the-art and sustainable implementation of
smart cities and practical challenges Includes sustainable
development of smart cities Presents detailed explanation of case
studies of smart cities of developed countries and developing
countries and their comparisons This book is aimed at researchers
and graduate students in Artificial Intelligence, Urban Planning,
and Information Technology Systems and Management.
The book acts as a guide; taking the reader into the smart system
domain and providing theoretical and practical knowledge along with
case studies in smart healthcare. The book uses a blend of
interdisciplinary approaches such as IoT, blockchain, augmented
reality, and virtual reality for the implementation of
cost-effective, real-time, and user-friendly solutions for
healthcare problems. Immersive Virtual and Augmented Reality in
Healthcare: An IoT and Blockchain Perspective presents the trends,
best practices, techniques, developments, sensors, materials, and
case studies that are using augmented and virtual reality
environments with the state-of-the-art latest technologies like
IoT, blockchain, and machine learning in the implementation of
healthcare systems. The book focuses on the design and
implementation of smart healthcare systems with major challenges to
further explore more robust and efficient healthcare solutions in
terms of low cost, faster algorithms, more sensitive IoT sensors,
faster data communication, and real-time solutions for treatment.
It discusses the use of virtual and augmented reality and how it
can provide user-friendly and interactive communication within
healthcare systems. Illustrated through case studies, the book
conveys how different hospitals and healthcare equipment providers
can adopt good practices found in the book to improve the
performance/productivity of their staff and system. The content is
rounded out by providing how IoT, blockchain, and artificial
intelligence can provide the framework for designing and/or
upgrading traditional healthcare systems by increasing security and
data privacy. A valuable resource for engineers working with
systems, the healthcare professionals involved in the design and
development of healthcare devices and systems, researcher scholars,
multidisciplinary scientists, students, and academics who are
wishing to explore the use of virtual and augmented reality in new
and existing healthcare systems.
This text provides novel smart network systems, wireless
telecommunications infrastructures, and computing capabilities to
help healthcare systems using computing techniques like IoT, cloud
computing, machine and deep learning Big Data along with smart
wireless networks. It discusses important topics, including
robotics manipulation and analysis in smart healthcare industries,
smart telemedicine framework using machine learning and deep
learning, role of UAV and drones in smart hospitals, virtual
reality based on 5G/6G and augmented reality in healthcare systems,
data privacy and security, nanomedicine, and cloud-based artificial
intelligence in healthcare systems. The book: * Discusses
intelligent computing through IoT and Big Data in secure and smart
healthcare systems. * Covers algorithms, including deterministic
algorithms, randomized algorithms, iterative algorithms, and
recursive algorithms. * Discusses remote sensing devices in
hospitals and local health facilities for patient evaluation and
care. * Covers wearable technology applications such as weight
control and physical activity tracking for disease prevention and
smart healthcare. This book will be useful for senior
undergraduate, graduate students, and academic researchers in areas
such as electrical engineering, electronics and communication
engineering, computer science, and information technology.
Discussing concepts of smart networks, advanced wireless
communication, and technologies in setting up smart healthcare
services, this text will be useful for senior undergraduate,
graduate students, and academic researchers in areas such as
electrical engineering, electronics and communication engineering,
computer science, and information technology. It covers internet of
things (IoT) implementation and challenges in healthcare
industries, wireless network, and communication-based optimization
algorithms for smart healthcare devices.
Integration of IoT with Cloud Computing for Smart Applications
provides an integrative overview of the Internet of Things (IoT)
and cloud computing to be used for the various futuristic and
intelligent applications. The aim of this book is to integrate IoT
and cloud computing to translate ordinary resources into smart
things. Discussions in this book include a broad and integrated
perspective on the collaboration, security, growth of cloud
infrastructure, and real-time data monitoring. Features: Presents
an integrated approach to solve the problems related to security,
reliability, and energy consumption. Explains a unique approach to
discuss the research challenges and opportunities in the field of
IoT and cloud computing. Discusses a novel approach for smart
agriculture, smart healthcare systems, smart cities and many other
modern systems based on machine learning, artificial intelligence,
and big data, etc. Information presented in a simplified way for
students, researchers, academicians and scientists, business
innovators and entrepreneurs, management professionals and
practitioners. This book can be great reference for graduate and
postgraduate students, researchers, and academicians working in the
field of computer science, cloud computing, artificial
intelligence, etc.
This powerful new volume explores the diverse and sometimes
unexpected roles that IoT and AI technologies played during the
recent COVID-19 global pandemic. The book discusses the how
existing and new state-of-the art technology has been and can be
applied for global health crises in a multitude of ways. The
chapters in Pandemic Detection and Analysis through Smart Computing
Technologies look at exciting technological solutions for virus
detection, prediction, classification, prevention, and
communication outreach. The book considers the various modes of
transmission of the virus as well as how technology has been
implemented for personalized healthcare systems and how it can be
used for future pandemics. The huge importance of social and mobile
communication and networks during the pandemic is addressed such as
in business, education, and healthcare; in research and
development; for health information and outreach; in social life;
and more. A chapter also addresses using smart computing for
forecasting the damage caused by COVID-19 using time series
analyses. This up-to-the-minute volume illuminates on the many ways
AI, IoT, machine learning, and other technologies have important
roles in the diverse challenges faced during COVID-19 and how they
can be enhanced for future pandemic situations. The volume will be
of high interest to those in different fields of computer science
and other domains as well as to data scientists, government
agencies and policymakers, doctors and healthcare professionals,
engineers, economists, and many other professionals. This book will
also be very helpful to faculty, students, and research scholars in
understanding the pre- and post-effect of this pandemic.
Focuses on new machine learning developments that can lead to newly
developed applications Uses a predictive and futuristic approach
which makes Machine Learning a promising tool for business
processes and sustainable solutions Promotes newer algorithms which
are more efficient and reliable for a new dimension in discovering
certain latent domains of applications Discusses the huge potential
in making better use of machines in order to ensure optimal
prediction, execution, and decision-making Offers many real-time
case studies
Covers evolutionary approaches to solve optimization problems in
biomedical engineering. Discusses IoT, Cloud computing, data
analytics in healthcare informatics. Provides computational
intelligence-based solution for diagnosis of diseases. Reviews
modelling and simulations in designing of biomedical equipment.
Promotes machine learning based approaches to improvements in
biomedical engineering problems.
This new volume, Cognitive Computing Systems: Applications and
Technological Advancements, explores the emerging area of
artificial intelligence that encompasses machine self-learning,
human-computer interaction, natural language processing, data
mining and more. It introduces cognitive computing systems,
highlights their key applications, discusses the technologies used
in cognitive systems, and explains underlying models and
architectures. Focusing on scientific work for real-world
applications, each chapter presents the use of cognitive computing
and machine learning in specific application areas. These include
the use of speech recognition technology, application of neural
networks in construction management, elevating competency in
education, comprehensive health monitoring systems, predicting type
2 diabetes, applications for smart agricultural technology, human
resource management, and more. With chapters from knowledgeable
researchers in the area of artificial intelligence, cognitive
computing, and allied areas, this book will be an asset for
researchers, faculty, advances students, and industry professionals
in many fields.
Computational Intelligence Techniques and Their Applications to
Software Engineering Problems focuses on computational intelligence
approaches as applicable in varied areas of software engineering
such as software requirement prioritization, cost estimation,
reliability assessment, defect prediction, maintainability and
quality prediction, size estimation, vulnerability prediction, test
case selection and prioritization, and much more. The concepts of
expert systems, case-based reasoning, fuzzy logic, genetic
algorithms, swarm computing, and rough sets are introduced with
their applications in software engineering. The field of knowledge
discovery is explored using neural networks and data mining
techniques by determining the underlying and hidden patterns in
software data sets. Aimed at graduate students and researchers in
computer science engineering, software engineering, information
technology, this book: Covers various aspects of in-depth solutions
of software engineering problems using computational intelligence
techniques Discusses the latest evolutionary approaches to
preliminary theory of different solve optimization problems under
software engineering domain Covers heuristic as well as
meta-heuristic algorithms designed to provide better and optimized
solutions Illustrates applications including software requirement
prioritization, software cost estimation, reliability assessment,
software defect prediction, and more Highlights swarm
intelligence-based optimization solutions for software testing and
reliability problems
This new volume explores the computational intelligence techniques
necessary to carry out different software engineering tasks.
Software undergoes various stages before deployment, such as
requirements elicitation, software designing, software project
planning, software coding, and software testing and maintenance.
Every stage is bundled with a number of tasks or activities to be
performed. Due to the large and complex nature of software, these
tasks can become costly and error prone. This volume aims to help
meet these challenges by presenting new research and practical
applications in intelligent techniques in the field of software
engineering. Computational Intelligence Applications for Software
Engineering Problems discusses techniques and presents case studies
to solve engineering challenges using machine learning, deep
learning, fuzzy-logic-based computation, statistical modeling,
invasive weed meta-heuristic algorithms, artificial intelligence,
the DevOps model, time series forecasting models, and more.
* Focuses on the computational intelligence techniques of security
system design * Covers applications and algorithms of discussed
computational intelligence techniques * Includes convergence-based
and enterprise integrated security systems with their applications
* Explains emerging laws, policies, and tools affecting the
landscape of cyber security * Discusses application of sensors
towards the design of security systems
Covers applications of Internet of Things (IoT) in Vehicular ad-hoc
network (VANETs). Discusses use of machine learning and other
computing techniques for enhancing performance of networks. Covers
game theory-based vertical handoffs in Heterogeneous Wireless
Networks. Examines monitoring and surveillance of vehicles through
the vehicular sensor network. Discusses theoretical approaches on
software-defined vehicular Ad-hoc network.
This unique book introduces a variety of techniques designed to
represent, enhance and empower multi-disciplinary and
multi-institutional machine learning research in healthcare
informatics. Providing a unique compendium of current and emerging
machine learning paradigms for healthcare informatics, it reflects
the diversity, complexity, and the depth and breadth of this
multi-disciplinary area. Further, it describes techniques for
applying machine learning within organizations and explains how to
evaluate the efficacy, suitability, and efficiency of such
applications. Featuring illustrative case studies, including how
chronic disease is being redefined through patient-led data
learning, the book offers a guided tour of machine learning
algorithms, architecture design, and applications of learning in
healthcare challenges.
Artificial Intelligence and Industry 4.0 explores recent
advancements in blockchain technology and artificial intelligence
(AI) as well as their crucial impacts on realizing Industry 4.0
goals. The book explores AI applications in industry including
Internet of Things (IoT) and Industrial Internet of Things (IIoT)
technology. Chapters explore how AI (machine learning, smart
cities, healthcare, Society 5.0, etc.) have numerous potential
applications in the Industry 4.0 era. This book is a useful
resource for researchers and graduate students in computer science
researching and developing AI and the IIoT.
This unique book introduces a variety of techniques designed to
represent, enhance and empower multi-disciplinary and
multi-institutional machine learning research in healthcare
informatics. Providing a unique compendium of current and emerging
machine learning paradigms for healthcare informatics, it reflects
the diversity, complexity, and the depth and breadth of this
multi-disciplinary area. Further, it describes techniques for
applying machine learning within organizations and explains how to
evaluate the efficacy, suitability, and efficiency of such
applications. Featuring illustrative case studies, including how
chronic disease is being redefined through patient-led data
learning, the book offers a guided tour of machine learning
algorithms, architecture design, and applications of learning in
healthcare challenges.
Researchers, academicians and professionals expone in this book
their research in the application of intelligent computing
techniques to software engineering. As software systems are
becoming larger and complex, software engineering tasks become
increasingly costly and prone to errors. Evolutionary algorithms,
machine learning approaches, meta-heuristic algorithms, and others
techniques can help the effi ciency of software engineering.
Due to the increase in the consumption of herbal medicine, there is
a need to know which scientifically based methods are appropriate
for assessing the quality of herbal medicines. Fingerprinting has
emerged as a suitable technique for quality estimation. Chemical
markers are used for evaluation of herbal medicines. Identification
and quantification of these chemical markers are crucial for
quality control of herbal medicines. This book provides updated
knowledge on methodology, quality assessment, toxicity analysis and
medicinal values of natural compounds.
Big data is a field of research that is growing rapidly, and as the
Covid-19 crisis has shown, health care is an area that could
benefit greatly from its increased use and application. Big data,
as derived partly from the internet of things and analysed
according to specific algorithms, has a large and beneficial role
to play in preventative medicine, in monitoring the health of
specific groups, and in improving diagnostics. Big Data Analytics
and Intelligence: A Perspective for Health Care focuses on various
areas of health care, ranging from nutrition to cancer, and
providing diverse perspectives on all of them. This book explores
the entire life-cycle of big data, from information retrieval to
analysis, and it shows how big data's applications can enhance,
streamline and improve services for patients and health-care
professionals. Each chapter focuses on a specific area of health
care and how big data is applicable to it, with background and
current examples provided.
Agriculture is one of the most fundamental human activities. As the
farming capacity has expanded, the usage of resources such as land,
fertilizer, and water has grown exponentially, and environmental
pressures from modern farming techniques have stressed natural
landscapes. Still, by some estimates, worldwide food production
needs to increase to keep up with global food demand. Machine
Learning and the Internet of Things can play a promising role in
the Agricultural industry, and help to increase food production
while respecting the environment. This book explains how these
technologies can be applied, offering many case studies developed
in the research world.
THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the
methods and tools for intelligent data analysis, this series aims
to narrow the increasing gap between data gathering and data
comprehension. Emphasis is also given to the problems resulting
from automated data collection in modern hospitals, such as
analysis of computer-based patient records, data warehousing tools,
intelligent alarming, effective and efficient monitoring. In
medicine, overcoming this gap is crucial since medical decision
making needs to be supported by arguments based on existing medical
knowledge as well as information, regularities and trends extracted
from big data sets.
Sustainable development helps undo the havoc that has been created
by human beings in the last few years in the name of development
and growth. It helps to promote a more social, environmental, and
economical way of living. There are many ways in which we all can
practice sustainable development in our daily lives and further
study is required. Multidisciplinary Approaches to Sustainable
Human Development focuses on all agendas of sustainable development
goals and offers approaches to develop a transdisciplinary
perspective that encompasses the natural, social, and human
sciences in the search for a sustainable society. Covering topics
such as green economy, social innovation, and climate change, this
premier reference work is ideal for environmentalists, government
officials, policymakers, researchers, scholars, academicians,
practitioners, instructors, and students.
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