Sambit Kumar Mishra – författare

This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology.

This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing.

The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology.

This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing.

The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.

Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively.

This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.

Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively.

This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems.

Features:

This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems.

Features:

This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This book covers online learning systems and their application to large-scale data along with the technological aspects of these processes and problem-solving methods.

Online Learning Systems: Methods and Applications with Large-Scale Data discusses the efficiency measurement and environmental impact of online education. The book offers a parametric evaluation and categorization of online learning systems and provides an exploration of big data ecosystems in cloud computing. Descriptive analytical methods that assist in finding solutions for big data challenges are also covered within the book.

The book is written for academicians, which includes teachers, students, and higher education policymakers who believe in transforming the education industry, as well as research scholars and those working in education technology and artificial intelligence. Industry professionals involved in education management and those working in e-Learning companies will also find this book useful.

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This book covers online learning systems and their application to large-scale data along with the technological aspects of these processes and problem-solving methods.

Online Learning Systems: Methods and Applications with Large-Scale Data discusses the efficiency measurement and environmental impact of online education. The book offers a parametric evaluation and categorization of online learning systems and provides an exploration of big data ecosystems in cloud computing. Descriptive analytical methods that assist in finding solutions for big data challenges are also covered within the book.

The book is written for academicians, which includes teachers, students, and higher education policymakers who believe in transforming the education industry, as well as research scholars and those working in education technology and artificial intelligence. Industry professionals involved in education management and those working in e-Learning companies will also find this book useful.

This book includes high-quality papers presented at the Second International Conference on Data Science and Management (ICDSM 2021), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from 19 to 20 February 2021. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.