Gitanjali Rahul Shinde – författare

Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.

Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.

This book presents the know-how of the real-time IoT application development activity including a basic understanding of the IoT architecture, use cases, smart computing, and the associated challenges in design and development of the IoT system. All the technical details related to protocol stack, technologies, and platforms used for the implementation are explained. It further includes techniques and case studies that include smart computing on the IoT–Cloud models along with test beds for experimentation purposes. The book aims at setting up the groundwork for the creation of applications that can help make day-to-day tasks simpler by meeting the needs of varied sectors like education, health care, agriculture, and so forth.Features:Covers IoT cloud convergence with a focus on complex industrial IoT case studiesDiscusses the broad background of IoT–Cloud convergence architectures and its fundamentals along with resource provisioning mechanismsEmphasizes the use of context in developing context-aware IoT solutionsPresents a novel C-model that explains the IoT application development phasesDiscusses a simplified convergence model that depicts the role of Cloud in an IoT applicationThis book aims at graduate students, researchers, and professionals getting started in the IoT field

This book presents the know-how of the real-time IoT application development activity including a basic understanding of the IoT architecture, use cases, smart computing, and the associated challenges in design and development of the IoT system. All the technical details related to protocol stack, technologies, and platforms used for the implementation are explained. It further includes techniques and case studies that include smart computing on the IoT–Cloud models along with test beds for experimentation purposes. The book aims at setting up the groundwork for the creation of applications that can help make day-to-day tasks simpler by meeting the needs of varied sectors like education, health care, agriculture, and so forth.Features:Covers IoT cloud convergence with a focus on complex industrial IoT case studiesDiscusses the broad background of IoT–Cloud convergence architectures and its fundamentals along with resource provisioning mechanismsEmphasizes the use of context in developing context-aware IoT solutionsPresents a novel C-model that explains the IoT application development phasesDiscusses a simplified convergence model that depicts the role of Cloud in an IoT applicationThis book aims at graduate students, researchers, and professionals getting started in the IoT field

This book presents some of the most advanced leading-edge technology for the fourth Industrial Revolution -- known as “Industry 4.0.” The book provides a comprehensive understanding of the interconnections of AI, IoT, big data and cloud computing as integral to the technologies that revolutionize the way companies produce and distribute products and the way local governments deliver their services. The book emphasizes that at every phase of the supply chain, manufactures are found to be interweaving AI, robotics, IoT, big data/machine learning, and cloud computing into their production facilities and throughout their distribution networks. Equally important, the authors show how their research can be applied to computer vision, cyber security, database and compiler theory, natural language processing, healthcare, education and agriculture.Presents the fundamentals of AI, IoT, and cloud computing and how they can be incorporatedin Industry 4.0 applicationsMotivates readers to address challenges in the areas of speech communication and signal processingProvides numerous examples, case studies, technical descriptions, and approaches of AI/ML

This book presents some of the most advanced leading-edge technology for the fourth Industrial Revolution -- known as “Industry 4.0.” The book provides a comprehensive understanding of the interconnections of AI, IoT, big data and cloud computing as integral to the technologies that revolutionize the way companies produce and distribute products and the way local governments deliver their services. The book emphasizes that at every phase of the supply chain, manufactures are found to be interweaving AI, robotics, IoT, big data/machine learning, and cloud computing into their production facilities and throughout their distribution networks. Equally important, the authors show how their research can be applied to computer vision, cyber security, database and compiler theory, natural language processing, healthcare, education and agriculture.Presents the fundamentals of AI, IoT, and cloud computing and how they can be incorporatedin Industry 4.0 applicationsMotivates readers to address challenges in the areas of speech communication and signal processingProvides numerous examples, case studies, technical descriptions, and approaches of AI/ML

This book discusses the use of converged technology, a rapidly growing area that enhancements smart devices, communication, Internet of things (IoT), and augmented reality (AR).

Big data modelling and visualization techniques of collected data play a vital role in the field of data science.

Big data modelling and visualization techniques of collected data play a vital role in the field of data science.

This book is focused on the impact of the COVID-19 pandemic on different sectors, i.e., education, real estate, health, and agriculture.

This book is focused on the impact of the COVID-19 pandemic on different sectors, i.e., education, real estate, health, and agriculture.