Computational Modelling Approaches to FinTech Innovation bridges the gap between technological advancement and financial systems by investigating the synergy between human intelligence and machine-driven models to drive innovation, resilience, and sustainability in finance. The book opens by grounding readers in the principles of Industry 5.0 and its implications for human-machine collaboration and green innovation. It then transitions into the evolution of management practices and enterprise digitalization, highlighting the journey from Industry 1.0 through to the current digital transformation. Later chapters explore the disruptive effects of Industry 5.0 on supply chains, production, and marketing strategies, before addressing the shifts in human resource management and the convergence of finance and technology. The final section offers insight into emerging technologies, including AI, IoT, Big Data, and Machine Learning, mapping their trajectory within modern industry frameworks. Key Features: Examine computational models driving FinTech transformation Explore Industry 5.0’s role in sustainable innovation and human-machine integration Analyze digital enterprise evolution and its management implications Investigate the effects of advanced technologies on supply chains and marketing Assess the fusion of finance and technology within organizational structures Uncover future trends through real-world applications of AI, IoT, and Big Data.

This timely and comprehensive volume explores the evolving concept of Society 5.0 — a forward-looking, human-centered society where cutting-edge technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), robotics, and augmented reality seamlessly integrate into daily life, healthcare, industry, and public services to enhance quality of life and social well-being. Industry 5.0, as a vital enabler of this vision, emphasizes collaborative interactions between humans and smart systems, driving innovations in personalized healthcare, sustainable industries, and connected communities. This first part of a multi-volume set provides readers with foundational insights into the principles, enabling technologies, and strategic opportunities shaping Industry 5.0 and Society 5.0. Edited contributions from subject matter experts offer a roadmap for harnessing Medical IoT (Internet of Medical Things) applications within this new societal framework. The book covers essential topics such as high-performance computing in healthcare decision support, AI-driven diagnostic solutions, cybersecurity in digital health systems, and ethical data practices in patient care. It also highlights emerging use cases, including IoT-enabled wearable devices for women’s security and smart diagnostic tools for early disease detection. Key features: Presents a detailed overview of Industry 5.0 and Society 5.0, their fundamentals, enabling technologies, and future prospects. Examines the role of Industry 5.0 in transforming medical and healthcare services through the integration of IoT and AI-driven solutions. Explores innovative applications such as AI-based diabetic retinopathy detection, IoT applications in digital healthcare, and patient-centric data ethics frameworks. Discusses advances in smart farming and sustainable industrial practices within the Industry 5.0 paradigm. Highlights opportunities for bridging research gaps in high-performance computing for holistic healthcare decision support. Provides use case studies on IoT-enabled healthcare security solutions and digital health systems.

This second installment in a two part series delves deeper into practical applications and domain-specific implementations of industry 5.0 principles, particularly in smart agriculture, next-generation manufacturing, and green computing. Through a multidisciplinary lens, the book examines the fusion of intelligent systems, medical IoT, and sustainable practices that contribute to societal well-being. Structured across three major themes—smart farming, current-era manufacturing, and green computing—the chapters provide in-depth analyses of enabling technologies, evolving methodologies, and real-world case studies. The narrative emphasizes co-evolution of industrial and social needs, encouraging readers to explore the transformative potential of AI, IoT, and Industry 5.0 innovations. Key Features • Analyzes AI-driven innovations in agriculture and sustainable food systems • Explores medical IoT, intelligent diagnostics, and healthcare transformation • Gives an understanding of Industry 5.0's impact on predictive maintenance and smart factories • Applies green computing and deep learning for sustainable development • Bridges theory and practice through real-world use cases and emerging solutions

Data Analytics and Artificial Intelligence for Predictive Maintenance in Industry 4.0 unites data science, machine learning, IIOT, and AI to enable predictive and prescriptive maintenance across manufacturing, energy, transportation, agriculture, and healthcare. With contributions from leading academics and practitioners, the book bridges foundational principles with cutting-edge industrial case studies ranging from digital twins and anomaly detection to federated learning and secure healthcare analytics. Key Features Explains fundamental concepts of data analytics, AI, and machine learning for predictive maintenance. Integrates IIoT, digital twins, federated learning, and blockchain into industrial maintenance strategies. Demonstrates real-world applications across manufacturing, energy, healthcare, and agriculture sectors. Analyzes optimization techniques, anomaly detection, condition monitoring, and RUL prediction models. Addresses security and ethical issues, including hardware protection and homomorphic encryption for healthcare. Maps future trends and emerging technologies driving predictive maintenance research.

AI-Driven Strategic Management: Navigating the Future of Business provides both conceptual clarity and practical guidance in AI-driven Strategic Management, equipping readers with the knowledge to harness AI in navigating uncertainty and sustaining long-term competitiveness. Beginning with an overview of the AI revolution in strategic management, the book discusses organizational enablers of AI adoption, including culture, talent, and leadership. Subsequent chapters examine how AI transforms decision-making, market forecasting, competitive positioning, and resource allocation across time, talent, and capital. The volume also integrates global perspectives, highlighting opportunities and challenges in emerging markets such as Africa. Real-world case studies reinforce theoretical insights, ensuring readers grasp both the opportunities and risks of AI in business strategy. Key Features: Explains the evolving role of AI in shaping modern strategic management. Demonstrates AI’s impact on decision-making, market forecasting, and competitive positioning. Addresses ethics, governance, and sustainability in AI-driven strategies. Highlights global perspectives with a focus on emerging markets. Provides practical insights through real-world case studies and applications.