This book gathers high-quality papers presented at Academia-Industry Consortium for Data Science (AICDS 2020), held in Wenzhou, China during 19 – 20 December 2020. The book presents views of academicians and also how companies are approaching these challenges organizationally. The topics covered in the book are data science and analytics, natural language processing, predictive analytics, artificial intelligence, machine learning, deep learning, big data computing, cognitive computing, data visualization, image processing, and optimization techniques.

Industry 4.0 is used interchangeably with the fourth industrial revolution and represents a new stage in the organization asnd control of the industrial value chain. Cyber-physical systems form the basis of industry 4.0 (e.g., 'smart machines'). They use modern control systems, have embedded software systems, can be addressed via IoT (the Internet of Things), and may use extensive data analytics and/or articifical inteligence systems to operate autonomously. The aim of this book is to provide detailed insights into the state of art techniques in AI, IoT, Blockchain technology and associated technologies which play a vital role in the implementation of a successful project for upcoming and practicing engineers. Owing to its multidisciplinary nature, Industry 4.0 is not a single topic but a combination of a multitude of technologies from different domains. Keeping this in mind the book includes the following topics: Artificial intelligence Internet of things Blockchain technology Digital manufacturing Robotics Cybersecurity The book will be a comprehensive guide to academicians and engineers who want to align with recent trends of fourth industrial revolution.

This book features selected papers presented at International Conference on Data Analytics and Computing (ICDAC 2022), organized by Department of Mathematics, College of Science and Technology, Wenzhou-Kean University, Wenzhou, China, held during May 28–29, 2022. This book includes state-of-the-art current trends in data science, data analytics optimization, soft computing and related areas. Its primary readers are postgraduate students, researchers and academic professionals.

BLOCKCHAIN and DEEP LEARNING for SMART HEALTHCARE The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare. The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare. Audience Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading.

Presently, we stand on the threshold of a technological revolution that will drastically change the way we live, work, and communicate with each other. By the current rate, scope, and complexity, this transformation will be as fundamental for society as any other technological paradigm change from the past. The industries which are more susceptible to change are technologically oriented industries including banking, finance, accounting, and auditing. One of the technological concepts of the technological revolution is the concept of the digital twin. The application of digital twins and AI as paired with Internet of Things technologies makes it possible to solve ESG problems on a completely different level (Li, 2019) for accounting firms and financial institutions. These include recycling on demand, rational energy consumption, smart surveillance cameras for crime tracking, and smart branch parking solutions, monitoring the wear and tear and conditions of financial technology infrastructures. Moreover, numerous researchers and practitioners emphasize the significance of innovating sustainable business models and operations (Geissdoerfer et al., 2018). The digital twin will allow businesses and financial institutions to minimize costs, boost customer service, and find new ways to generate revenue. DTW is accessible now more than ever, and many reputable and innovative companies such as Tesla, Ericsson, and Siemens have adopted it with varying success. Therefore, this book examines the opportunities, challenges, and risks of artificial intelligence-augmented digital twins for financial operations, innovation, and sustainable development. It focuses on AI and digital twin technologies to furnish solutions for the current industrial revolution including the Metaverse. Henceforth, this book aims to encourage authors to submit multi-disciplinary chapters indicating the current scholarly challenges about the applications and potential of artificial intelligence and digital twins in accounting, finance, and banking.