Naveen Chilamkurti – författare

Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today's Intelligent Transportation System (ITS). It explores the design goals, challenges, and frameworks for modeling an ITS network, discussing vehicular network model technologies, mobility management architectures, and routing mechanisms and protocols. It looks at the Internet of Vehicles, the vehicular cloud, and vehicular network security and privacy issues.

The book investigates cooperative vehicular systems, a promising solution for addressing current and future traffic safety needs, also exploring cooperative cognitive intelligence, with special attention to spectral efficiency, spectral scarcity, and high mobility. In addition, users will find a thorough examination of experimental work in such areas as Controller Area Network protocol and working function of On Board Unit, as well as working principles of roadside unit and other infrastructural nodes.

Finally, the book examines big data in vehicular networks, exploring various business models, application scenarios, and real-time analytics, concluding with a look at autonomous vehicles.

Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book''s accessibility more extensively.

Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions.

The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed.

FEATURES

This book is suitable for graduates, academics, researchers, IT professionals, and industry experts.

Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book''s accessibility more extensively.

Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions.

The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed.

FEATURES

This book is suitable for graduates, academics, researchers, IT professionals, and industry experts.

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.

Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information.

Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.

Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information.

Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

The primary goal of this book is to address the issues faced by teachers in the adoption of digital tools into their teaching and their students learning. This book also addresses the issues confronting educators in the integration of digital technologies into their teaching and their students’ learning. Such issues include a skepticism of the added value of technology to educational learning outcomes, the perception of the requirement to keep up with the fast pace of technological innovation, a lack of knowledge of affordable educational digital tools and a lack of understanding of pedagogical strategies to embrace digital technologies in their teaching. This book presents theoretical perspectives of learning and teaching today’s digital students with technology and proposes a pragmatic and sustainable framework for teachers’ professional learning to embed digital technologies into their repertoire of teaching strategies in a systematic, coherent and comfortable manner so that technology integration becomes an almost effortless pedagogy in their day-to-day teaching.

Some of the objectives are given below:

The primary goal of this book is to address the issues faced by teachers in the adoption of digital tools into their teaching and their students learning. This book also addresses the issues confronting educators in the integration of digital technologies into their teaching and their students’ learning. Such issues include a skepticism of the added value of technology to educational learning outcomes, the perception of the requirement to keep up with the fast pace of technological innovation, a lack of knowledge of affordable educational digital tools and a lack of understanding of pedagogical strategies to embrace digital technologies in their teaching. This book presents theoretical perspectives of learning and teaching today’s digital students with technology and proposes a pragmatic and sustainable framework for teachers’ professional learning to embed digital technologies into their repertoire of teaching strategies in a systematic, coherent and comfortable manner so that technology integration becomes an almost effortless pedagogy in their day-to-day teaching.

Some of the objectives are given below:

Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research. It also presents an outline of the recent breakthroughs in the application of AI in healthcare, describes a roadmap to building effective, reliable, and safe AI systems, and discusses the possible future direction of AI augmented healthcare systems. AI has countless applications in healthcare. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency; AI has been a boon to the healthcare industry.

Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research. It also presents an outline of the recent breakthroughs in the application of AI in healthcare, describes a roadmap to building effective, reliable, and safe AI systems, and discusses the possible future direction of AI augmented healthcare systems. AI has countless applications in healthcare. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency; AI has been a boon to the healthcare industry.

It is well-established that every organization is founded with a specific purpose and goals. Virtually all business organizations obtain measurements and metrics dealing with outcomes and results. However, what is reflected on the balance sheet does not necessarily show the actual worth of the organizations and ensure their survival and sustainability. Thus, the question arises, what exactly makes the organizations sustainable and thriving in an ever-changing environment? There are several examples of companies like Faber-Castell, Bank of Ireland, Chivas, DuPont and many more which have been able to sustain and survive over more than 200 years and still have a successful existence in the present era. Thus, it is important for the organization to pay equal attention to its three bottom lines, i.e., people, profit and planet for its sustainability, which not only meet the needs of the present generation but should have a futuristic approach as well.

In the present era, organizations are adopting a new normal working dynamic and coping with the post-pandemic situations to sustain themselves in the business environment. Technology plays a significant role in this new working dynamic, and cutting-edge technologies like machine learning, artificial intelligence, blockchain,ChatGPT, Internet of Things, and much more effectively facilitate human functioning at work. The book aims to contribute to understanding and developing sustainable human resource management processes and practices aligned with recent technologies. It highlights the interconnection among the three bottom-line sustainable approaches for the growth and development of the organization.

Topics discussed in this book include:

• Disruptive Technologies and HR Sustainability

• Convergence of Innovative Technologies, HR and Organizational Growth

• Triple bottom-line Sustainability for HRM

• Business-oriented Talent analytics and HR Sustainability

• Role of Leadership in sustainable HRM practices.

It is well-established that every organization is founded with a specific purpose and goals. Virtually all business organizations obtain measurements and metrics dealing with outcomes and results. However, what is reflected on the balance sheet does not necessarily show the actual worth of the organizations and ensure their survival and sustainability. Thus, the question arises, what exactly makes the organizations sustainable and thriving in an ever-changing environment? There are several examples of companies like Faber-Castell, Bank of Ireland, Chivas, DuPont and many more which have been able to sustain and survive over more than 200 years and still have a successful existence in the present era. Thus, it is important for the organization to pay equal attention to its three bottom lines, i.e., people, profit and planet for its sustainability, which not only meet the needs of the present generation but should have a futuristic approach as well.

In the present era, organizations are adopting a new normal working dynamic and coping with the post-pandemic situations to sustain themselves in the business environment. Technology plays a significant role in this new working dynamic, and cutting-edge technologies like machine learning, artificial intelligence, blockchain,ChatGPT, Internet of Things, and much more effectively facilitate human functioning at work. The book aims to contribute to understanding and developing sustainable human resource management processes and practices aligned with recent technologies. It highlights the interconnection among the three bottom-line sustainable approaches for the growth and development of the organization.

Topics discussed in this book include:

• Disruptive Technologies and HR Sustainability

• Convergence of Innovative Technologies, HR and Organizational Growth

• Triple bottom-line Sustainability for HRM

• Business-oriented Talent analytics and HR Sustainability

• Role of Leadership in sustainable HRM practices.

This book offers a comprehensive overview of the current state of cybersecurity in smart cities and explores how AI and IoT technologies can be used to address cybersecurity challenges. It discusses the potential of AI for threat detection, risk assessment, and incident response, as well as the use of IoT sensors for real-time monitoring and data analysis in the context of smart cities. It includes case studies from around the world to provide practical insights into the use of AI and IoT technologies for enhancing cybersecurity in different contexts and highlight the potential benefits of these technologies for improving the resilience and security of smart cities.

Key Features:

Postgraduate students and researchers in the departments of Computer Science, working in the areas of IoT and Smart Cities will find this book useful.

This book offers a comprehensive overview of the current state of cybersecurity in smart cities and explores how AI and IoT technologies can be used to address cybersecurity challenges. It discusses the potential of AI for threat detection, risk assessment, and incident response, as well as the use of IoT sensors for real-time monitoring and data analysis in the context of smart cities. It includes case studies from around the world to provide practical insights into the use of AI and IoT technologies for enhancing cybersecurity in different contexts and highlight the potential benefits of these technologies for improving the resilience and security of smart cities.

Key Features:

Postgraduate students and researchers in the departments of Computer Science, working in the areas of IoT and Smart Cities will find this book useful.

Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.

The traditional framework of Human Resource Management (HRM) primarily consists of four functions: Human Resource Planning, Recruitment and Selection, Training and Development and Performance Management Systems which help businesses in hiring, motivating and retaining employees. The introduction of Artificial Intelligence (AI) has changed all of these aspects.

The Adoption and Effect of Artificial Intelligence on Human Resources Management Series sets out a blended approach towards different functions of HRM and AI, reflecting upon: HR data privacy; data security; diversity and inclusion using AI; and sustainable AI-HR practices. This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.