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 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 incorporated in Industry 4.0 applications Motivates readers to address challenges in the areas of speech communication and signal processing Provides numerous examples, case studies, technical descriptions, and approaches of AI/ML

Covers IoT-cloud convergence with a focus on complex industrial IoT case studies Discusses the broad background of IoT-cloud convergence architectures and their fundamentals along with resource provisioning mechanisms Emphasizes the use of context in developing context aware IoT solutions Presents a novel C-model that explains the IoT application development phases Discusses a simplified convergence model that depicts the role of cloud in an IoT application

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.

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). The book also explores the need for convergence of IoT and AR for various purposes, like personalized services, context awareness, and bridging the gap between the physical and digital world. Furthermore, it examines the implementation of IoT and AR in use cases to define pathways that allow application developers to design modern solutions to satisfy requirements like scalability, abstraction and security. Featuring an introduction, and covering sensing techniques, and effective architecture in AR-based IoT real-time use cases, the book also addresses the issues and challenges in designing standard architecture and middleware to support diverse applications. Given its scope, it is a valuable resource for teachers and students in engineering, as well as researchers, developers, and users working in multi-disciplinary areas.

This book is focused on the impact of the COVID-19 pandemic on different sectors, i.e., education, real estate, health, and agriculture. The lockdown has been announced to control the spread of COVID-19 infections, however people/industries/organizations were not ready for lockdown and it has greatly affected their growth. The front workers in the healthcare sector suffered a lot as major responsibilities they needed to carry on. The education sector is also hampered due to the pandemic as schools, colleges were closed and teaching, examinations were carried out on online platforms. These platforms were new to teachers as well as students. The real estate sector faced tremendous loss in this pandemic as people were scared and no one ready to invest their money in such an uncertain time. The agriculture filed is also suffered as raw materials required for agriculture were not available readily due to pandemic. This book presents a survey that is conducted to understand the impact of COVID-19 on the quality of work-life in various sectors. The survey is focused majorly on four sectors, i.e. education, healthcare, real estate and agriculture. Data analysis is done based on responses of survey and mathematical modeling is provided for each case study.