Artificial Intelligence, Big Data, Algorithms and Industry 4.0 in Firms and Clusters


Book Description

This volume offers a wide-ranging discussion on the interrelations among AI, algorithms, big data, and Industry 4.0 to understand the importance of these new paradigms for the development of firms, districts, clusters, cities, regions, and innovation. Drawing on theoretical, empirical, and qualitative studies and using local perspectives, the chapters in this book explore theoretical aspects of AI and its evolution in social sciences, focusing on industry 4.0, smart cities, big data, and other related topics. They examine the role of industrial robots in employment, productivity, and knowledge absorption in industrial districts. They also discuss innovation in the context of local production systems, AI ecosystems, and the growth and potential of the Metaverse. Taken together, the book offers insights to help understand the new dynamics generated by the advent of these technologies and how they may affect regions, cities, clusters, industries, and organizations, and identifies avenues for future research in the development of new trajectories for clusters and firms. This book will be a key resource for scholars and advanced students in the fields of economics, geography, architecture, planning, and management as well as for interdisciplinary researchers who want to learn more about the development of new technologies, the relevance of AI, Big Data and I4.0 for firms and in relation to their adoption in clusters. This book was originally published as a special issue of European Planning Studies.




The Economics of Artificial Intelligence


Book Description

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.




Artificial Intelligence for Big Data


Book Description

Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.




Artificial Intelligence, Big Data, Algorithms and Industry 4.0 in Firms and Clusters


Book Description

This volume offers a diverse discussion on the interrelations among AI, algorithms, big data, and Industry 4.0 to understand the importance of these paradigms for the development of firms, districts, clusters, cities, regions, and innovation. This book was originally published as a special issue of European Planning Studies.




Industry 4.0 Interoperability, Analytics, Security, and Case Studies


Book Description

All over the world, vast research is in progress on the domain of Industry 4.0 and related techniques. Industry 4.0 is expected to have a very high impact on labor markets, global value chains, education, health, environment, and many social economic aspects. Industry 4.0 Interoperability, Analytics, Security, and Case Studies provides a deeper understanding of the drivers and enablers of Industry 4.0. It includes real case studies of various applications related to different fields, such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, machine learning, virtualization, decentralization, blockchain, fog computing, and many other related areas. Also discussed are interoperability, design, and implementation challenges. Researchers, academicians, and those working in industry around the globe will find this book of interest. FEATURES Provides an understanding of the drivers and enablers of Industry 4.0 Includes real case studies of various applications for different fields Discusses technologies such as cyber physical systems (CPS), Internet of Things (IoT), cloud computing, machine learning, virtualization, decentralization, blockchain, fog computing, and many other related areas Covers design, implementation challenges, and interoperability Offers detailed knowledge on Industry 4.0 and its underlying technologies, research challenges, solutions, and case studies




Big Data Applications in Industry 4.0


Book Description

Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making




Artificial intelligence, Big data, blockchain and 5G for the digital transformation of the healthcare industry


Book Description

?Artificial intelligence, Big data, Blockchain and 5G for Digital Transformation of Healthcare Industry provides insights on the successes and failures in the field of IT and digital health during the pandemic and analyzes the lessons from these cases. The social and economic recovery after the pandemic requires urgent solutions for citizens, companies and economies around the world. From research centers, labs, hospitals and academia, researchers and academics are working collaboratively to explore new views and frameworks to develop solutions for emergent problems. Artificial intelligence, Big data, blockchain and 5G for digital transformation of healthcare industry includes cases highlighting the application of digital healthcare solutions from around the world. In 23 Chapters this book delivers a collection of relevant innovative research on digital healthcare, with a three mains goals: 1) study the successes and failures in the field of IT and digital health during the pandemic, and analyze the lessons from these cases; 2) discuss the latest advances in the field of digital healthcare, with a special focus on Artificial Intelligence, Big Data, Blockchain and 5G; and 3) discuss implications for main stakeholders (patients, doctors, IT experts, directors, policy managers. The global outbreak caused by covid-19 caused global disruption in societies, healthcare systems, and economies around the world. This book provides insight to Researchers, clinicians, CEOs and policy makers who need to learn from the failures and successes and exploit the potential of advanced information technologies to build stronger healthcare systems, better quality healthcare services, and more resilient societies. Delivers a collection of relevant innovative research on digital healthcare Discusses the latest advances in the field of digital healthcare, with a special focus on Artificial Intelligence, Big Data, Blockchain, and 5G Provides current lessons learned from the pandemic Includes case studies and experiences from around the world, including Asia, Europe, Gulf Region, Latin America, the United States, and more




Implementing Industry 4.0 in SMEs


Book Description

This open access book addresses the practical challenges that Industry 4.0 presents for SMEs. While large companies are already responding to the changes resulting from the fourth industrial revolution , small businesses are in danger of falling behind due to the lack of examples, best practices and established methods and tools. Following on from the publication of the previous book ‘Industry 4.0 for SMEs: Challenges, Opportunities and Requirements’, the authors offer in this new book innovative results from research on smart manufacturing, smart logistics and managerial models for SMEs. Based on a large scale EU-funded research project involving seven academic institutions from three continents and a network of over fifty small and medium sized enterprises, the book reveals the methods and tools required to support the successful implementation of Industry 4.0 along with practical examples.




The Elements of Big Data Value


Book Description

This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.




WIPO Technology Trends 2019 - Artificial Intelligence


Book Description

The first report in a new flagship series, WIPO Technology Trends, aims to shed light on the trends in innovation in artificial intelligence since the field first developed in the 1950s.