The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.

Forward thinking resource discussing emerging AI and IoT technologies and how they are applied to Industry 4.0 Topics in Artificial Intelligence Applied to Industry 4.0 discusses the design principles, technologies, and applications of emerging AI and IoT solutions on Industry 4.0, explaining how to make improvements in infrastructure through emerging technologies. Providing a clear connection with different technologies such as IoT, Big Data, AR and VR and Blockchain, this book presents security, privacy, trust, and other issues whilst delving into real-world problems and case studies. The text takes a highly practical approach, with a clear insight on how readers can increase productivity by drastically shortening the time period between the development of a new product and its delivery to customers in the market by 50%. This book also discusses how to save energy across systems to ensure competitiveness in a global market, and become more responsive in how they produce products and services for their consumers, such as by investing in flexible production lines. Written by highly qualified authors, Topics in Artificial Intelligence Applied to Industry 4.0 explores sample topics such as: Quantum machine learning, neural network implementation, and cloud and data analytics for effective analysis of industrial data Computer vision, emerging networking technologies, industrial data spaces, and an industry vision for 2030 in both developing and developed nations Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart environment Future professions in agriculture, medicine, education, fitness, R&D, and transport and communication as a result of new technologies Aimed at researchers and students in the interdisciplinary fields of Smart Manufacturing and Smart Applications, Topics in Artificial Intelligence Applied to Industry 4.0 provides the perfect overview of technology from the perspective of modern society and operational environment.

Industry 4.0 Vision for the Supply of Energy and Materials Explore the impact of Industry 4.0 technologies on the supply chain with this authoritative text written by a leader in his field In Industry 4.0 Vision for the Supply of Energy and Materials, distinguished researcher and editor, Dr. Mahdi Sharifzadeh, delivers thematic, analytic, and applied discussions of the Industry 4.0 vision for supply chain design and operation. The book compiles all current aspects and emerging notions of Industry 4.0 into clusters of "enablers" and "analytics" of Supply Chain 4.0. Their multifaceted and highly interconnected nature is discussed at length, as are their diverse range of applications. You will discover uses of these new technologies ranging from the supply of conventional energy networks to renewables, pharmaceuticals, and additive manufacturing. You will also learn about their implications for economic prosperity and environmental sustainability. For each sector, this book scrutinizes current industrial practice and discusses developing concepts. Finally, the book concludes with potential future research directions of interest to industry practitioners and academics alike. Readers will also benefit from the inclusion of: A thorough introduction to connectivity through wireless communications and remote sensors An exploration of blockchains and smart contracts, as well as robotics and automation and cloud computing Practical discussions of supply chain analytics, including big data, machine-learning, and artificial intelligence, as well as supply chain modeling, optimization, and control A concise treatment of Industry 4.0 applications in supply chain design and operation, including the circular economy and the power industry An analysis of the oil, gas, and petrochemical industry, the pharmaceutical industry, and additive manufacturing Perfect for PhD-level and Postdoctoral researchers and industrial researchers, Industry 4.0 Vision for the Supply of Energy and Materials will also earn a place in the libraries of working professionals with an interest in the quantitative analysis of Supply Chain 4.0 concepts and techniques.

The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges.

This book presents a vital method for companies to connect with potential clients andconsumers in the digital era of Online Social Networks (OSNs), utilizing the strengthof well-known social networks and AI to achieve success through fostering brandsupporters, generating leads, and enhancing customer interactions. There are currently 4.8 billion Online Social Network (OSN) users worldwide. Online Social Networks in Business Frameworks presents marketing through online social networks (OSNs), which is a potent method for companies of all sizes to connect with potential clients and consumers. If visitors are not on OSN sites like Facebook, Twitter, and LinkedIn, they are missing out on the fact that people discover, learn about, follow, and purchase from companies on OSNs. Excellent OSN advertising may help a company achieve amazing success by fostering committed brand supporters and even generating leads and revenue. A type of digital advertising known as social media marketing (SMM) makes use of the strength of well-known social networks to further advertise and establish branding objectives. Nevertheless, it goes beyond simply setting up company accounts and tweeting whenever visitors feel like it. Preserving and improving profiles means posting content that represents the company and draws in the right audience, such as images, videos, articles, and live videos, addressing comments, shares, and likes while keeping an eye on the reputation to create a brand network, and following and interacting with followers, clients, and influencers.

In the constant battle between human intelligence and machine intelligence, machines are close to surpassing human intelligence. The unrestrained use of digital technologies in automating processes is one of the prime advantages of the third industrial revolution. As a result, all developed and developing nations have started to digitalize mundane tasks. Thus, digital technologies for information and communication technologies (ICT) have achieved high market space in terms of infrastructure building, employment generation, education sector reforms, funds mobilization, electronic governance, hardware manufacturing, software development, etc. Hence, it is evident that every segment of society has been penetrated by ICT or digitalization. This book attempts to spotlight areas where AI is thriving. FEATURES Impact of digitalization and AI on governance Novel AI practices being followed across the global community in security, healthcare, crime prevention and detection, education, agriculture, sensor networks, etc. Innovative techniques that can be adopted to ensure better quality and better delivery of services to the society Avenues for further research by the research community and student fraternity This book is a guide for university students (especially those from technical backgrounds), industries, NGOs, and policy makers.

Get up to speed with how the latest knowledge management and industry 4.0 technologyhelp make enterprises secure, controlled, and optimized for a better future. This book focuses on how the practices of Industrial Revolution 4.0 and knowledge management interact to create value. In recent years, value chain relationships and related activities have utilized new technologies so that existing conceptual frameworks require a roadmap for innovation strategies and effective implementation. The chapters in this book include case studies contributed by researchers and industry practitioners that showcase the impact of practices and challenges presented by technological changes, upgrading of old systems, and internal and external factors. Knowledge Management and Industrial Revolution 4.0 describes how knowledge management impacts the automation of the industry in secure, controlled, and optimized ways. For instance, the use of the latest technologies and sensors can lead to significant time and cost savings, and operators can utilize their machines and equipment from remote locations. The Industrial Revolution 4.0 incorporates the latest technologies for automation and, in many cases, the result is similar to working from home, even in manufacturing. The use of deep learning should offer many quality control benefits. Furthermore, blockchain technology can help the industry with automation in secure and transparent ways. Apart from industry automation, other departments like human resources can also use effective knowledge management for better outcomes. The use of HR knowledge management allows employees to find and access the information they require without the assistance of the HR department. The book focuses on every aspect of the industry to help all the stakeholders of an organization. The benefits include a reduction in time required for accessing information, easier training, decreased operational expenses, improved stakeholders’ satisfaction, faster problem-solving, increased pace of innovation, simpler employee review and progress reports. Audience The book will have a wide audience within academia, education, businesses, and industrial organizations, especially those who are undergoing industry 4.0 changes to optimize for a better future.

Understanding consumer behavior in today's digital landscape is more challenging than ever. Businesses must navigate a sea of data to discern meaningful patterns and correlations that drive effective customer engagement and product development. However, the ever-changing nature of consumer behavior presents a daunting task, making it difficult for companies to gauge the wants and needs of their target audience accurately. Enhancing and Predicting Digital Consumer Behavior with AI offers a comprehensive solution to this pressing issue. A strong focus on concepts, theories, and analytical techniques for tracking consumer behavior changes provides the roadmap for businesses to navigate the complexities of the digital age. By covering topics such as digital consumers, emotional intelligence, and data analytics, this book serves as a timely and invaluable resource for academics and practitioners seeking to understand and adapt to the evolving landscape of consumer behavior.

This book presents research in big data analytics (BDA) for business of all sizes. The authors analyze problems presented in the application of BDA in some businesses through the study of development methodologies based on the three approaches – 1) plan-driven, 2) agile and 3) hybrid lightweight. The authors first describe BDA systems and how they emerged with the convergence of Statistics, Computer Science, and Business Intelligent Analytics with the practical aim to provide concepts, models, methods and tools required for exploiting the wide variety, volume, and velocity of available business internal and external data - i.e. Big Data – and provide decision-making value to decision-makers. The book presents high-quality conceptual and empirical research-oriented chapters on plan-driven, agile, and hybrid lightweight development methodologies and relevant supporting topics for BDA systems suitable to be used for large-, medium-, and small-sized business organizations.