LEADER 11005nam 22004693 450 001 9910806192703321 005 20240203060212.0 010 $a981-9981-18-2 035 $a(MiAaPQ)EBC31096194 035 $a(Au-PeEL)EBL31096194 035 $a(EXLCZ)9930157159200041 100 $a20240203d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDigital Transformation $eIndustry 4. 0 to Society 5. 0 205 $a1st ed. 210 1$aSingapore :$cSpringer Singapore Pte. Limited,$d2024. 210 4$d©2024. 215 $a1 online resource (365 pages) 225 1 $aDisruptive Technologies and Digital Transformations for Society 5. 0 Series 311 08$aPrint version: Kumar, Avadhesh Digital Transformation Singapore : Springer Singapore Pte. Limited,c2024 9789819981175 327 $aIntro -- Preface -- Introduction -- Contents -- Editors and Contributors -- Abbreviations -- 1 Evolution of Industry 4.0 and Its Fundamental Characteristics -- 1 Introduction -- 1.1 Industry 4.0 Introduction -- 1.2 Industry 4.0 Definitions -- 1.3 Benefits of Industry 4.0 -- 1.4 Motivations Behind the Evolution of Industry 4.0 -- 2 Industry 4.0 Concepts, State of Arts, and Challenges -- 2.1 Basic Components of Industry 4.0 -- 2.2 Characteristics of Industry 4.0 -- 2.3 State of Arts -- 2.4 Conceptualizing the Fourth Industrial Revolution -- 2.5 Goals to Consummate Industry 4.0 -- 2.6 Drivers of Industry 4.0 -- 2.7 Implementation Challenges of Industry 4.0 -- 3 Methodologies in Industry 4.0 -- 3.1 Validating Technologies/Base Technologies of Industry 4.0 -- 3.2 Nine Technology Peers of Industry 4.0 -- 3.3 Architectural Design of Industry 4.0 -- 3.4 Artificial Intelligence in Industry 4.0 -- 3.5 Processes and Interaction in Industry 4.0 -- 4 Applications, Use Cases, and Projects of Industry 4.0 -- 4.1 Influence of 5G Technologies on Industry 4.0 -- 4.2 5G Tech Support for Industry 4.0 -- 4.3 Industry 4.0 Application Scenarios Accredited by 5G -- References -- 2 Transportation System Using Deep Learning Algorithms in Industry 4.0 Towards Society 5.0 -- 1 Introduction -- 2 Deep Learning Techniques/Algorithms -- 2.1 Recursive Neural Network -- 2.2 Recurrent Neural Network (RNN) -- 2.3 Convolution Neural Network -- 2.4 Deep Generative Network -- 3 Transportation Network Representation Using Deep Learning -- 4 Various Domains that are Being Revolutionized by Deep Learning -- 4.1 Self-Driving Cars -- 4.2 Traffic Congestion Identification and Prediction -- 4.3 Predicting Vehicle Maintenance Needs -- 4.4 Public Transportation Optimization -- 5 Architecture of Convolutional Neural Network (CNN) Model -- 5.1 High-Resolution Data Collection. 327 $a5.2 CNN for Crash Predict -- 6 Traffic Flow Prediction -- 7 Urban Traffic Flow Prediction -- 8 Open Research Challenges and Future Directions -- 9 Conclusion -- References -- 3 A Brief Study of Adaptive Clustering for Self-aware Machine Analytics -- 1 Introduction -- 2 Clustering -- 2.1 Types of Clustering -- 3 Traditional Clustering Algorithm versus Bio-inspired Clustering -- 4 Self-aware Clustering -- 5 Adaptive Clustering for Industry 4.0 -- 5.1 Adaptive Clustering in Mobile Computing -- 5.2 Adaptive Clustering in Wireless Network -- 5.3 Adaptive Clustering in IoT -- 5.4 Adaptive Clustering in Cloud -- 5.5 Role of Clustering in Machine Analytics -- 5.6 Importance of Adaptive Clustering for Self-aware in Machine Analytics -- 6 Result and Discussion -- 7 Conclusion -- References -- 4 Managing Healthcare Data Using ML Algorithms and Society 5.0 -- 1 Introduction -- 2 Skin Cancer -- 2.1 Human Skin Cancer -- 2.2 Obstacles to Detecting Skin Lesions -- 2.3 Literature Survey -- 3 Methodology -- 3.1 Image Preprocessing -- 3.2 Median Filter -- 3.3 Lesion Segmentation -- 3.4 Feature Extraction -- 3.5 Feature Reduction -- 3.6 Image Classification -- 4 Digital Health Using Federated Learning -- 4.1 Federated Learning's Statistical Challenges -- 4.2 Federated Learning Communication Efficiency -- 4.3 Security and Privacy -- 4.4 Multiple-Party Computation with Security -- 4.5 Privacy Differential -- 4.6 Applications -- 5 Communal Issues that Concern Various Applications of ML in Medicine -- 5.1 Legislation -- 5.2 Interpretability and Explainability -- 5.3 Privacy and Anonymity -- 5.4 Ethics and Fairness -- 6 Conclusion -- References -- 5 Cloud Computing-Everything as a Cloud Service in Industry 4.0 -- 1 Introduction -- 1.1 Introduction to Cloud Computing -- 1.2 Why We Need Cloud Computing? -- 2 Different Services in Cloud Computing. 327 $a2.1 Infrastructure as a Service: [IaaS] -- 2.2 Platform as Service: [PaaS] -- 2.3 Software as a Service: [SaaS] -- 3 Different Cloud Models -- 3.1 Public Cloud -- 3.2 Private Cloud -- 3.3 Hybrid Cloud -- 3.4 Multi Cloud -- 4 Applications of Cloud -- 4.1 Cloud in Business Sector -- 4.2 Cloud in Education System -- 4.3 Cloud in Medical and Healthcare -- 4.4 Cloud in Software Development -- 5 Comparison of Various Cloud Platforms -- 5.1 Resource Allocation on All Models -- 6 Conclusion -- References -- 6 Glimpse of Cognitive Computing Towards Society 5.0 -- 1 Introduction -- 1.1 A Glimpse into the Evolution off Societies -- 1.2 The Need for Society 5.0 -- 1.3 The Working of Society 5.0 as A Solution to Social Problems -- 1.4 Attaining Society 5.0 -- 2 The Implementation and Impact of Society 5.0 -- 2.1 Infrastructure -- 2.2 Mobility -- 2.3 Health -- 2.4 Education -- 2.5 Manufacturing -- 2.6 Agriculture -- 2.7 Energy -- 2.8 Disaster Prevention -- 2.9 Food Products -- 2.10 Fintech -- 2.11 Tourism -- 2.12 Cyber Space -- 3 Cognitive Computing in a Nutshell -- 3.1 Characteristics of Cognitive Computing -- 3.2 The Differences Between Artificial Intelligence and Cognitive Computing -- 3.3 Advantages of Cognitive Computing -- 3.4 Caveats of Cognitive Computing -- 4 Use Case Scenarios of Cognitive Computing at Work -- 4.1 Intelligent Assistant-Cora (Royal Bank of Scotland-RBS) -- 4.2 Personal Travel Planner by WayBlazer -- 4.3 Cafewell-A Healthcare Concierge by Welltok -- 4.4 Fantasy Football Team Decision Maker by Edge up Sports -- 5 Conclusion -- 5.1 Future Scope and Discussion -- References -- 7 Big Data Analytics in Industry 4.0 in Legal Perspective: Past, Present and Future -- 1 Introduction -- 2 The Basic Flow of Big Data's Past, Present, and Future -- 2.1 The Origins of Data -- 2.2 The Dawn of Statistics -- 2.3 Modern Data Storage in Its Infancy. 327 $a2.4 Business Intelligence's Beginnings -- 2.5 1964 -- 2.6 Data Centres Are Getting Started -- 2.7 The Internet's First Years -- 2.8 Big Data's Earliest Concepts -- 2.9 Big Data in the Twenty-First Century -- 3 From Industry 4.0 to Society 4.0 -- 4 From Industry 4.0 to Market 4.0 -- 4.1 Phases of Marketing 4.0 -- 5 Literature Review -- 6 The Legal Constraints of Big Data Analytics -- 7 Analysis of Data Protection Principles in the Context of Big Data -- 8 Big Data and Black Data Affairs -- 8.1 Advantages -- 8.2 Disadvantages -- 9 Legal Standpoint-Comparative Reflection -- 9.1 United States of America -- 9.2 United Kingdom -- 9.3 India -- 9.4 Brazil -- 9.5 Bangladesh -- 9.6 Australia -- 9.7 Conclusion -- References -- 8 Unified Architectural Framework for Industrial Internet of Things -- 1 Introduction -- 2 The Technologies Associated with IIoT -- 2.1 Industry 4.0 -- 2.2 Cyber-Physical Systems (CPS) -- 3 Industrial Automation and Control Systems (IACS) -- 4 Literature Review -- 5 IoT to IIoT -- 6 Basic Overview of IIoT Architecture -- 7 IIoT Architecture -- 8 IIoT Framework -- 9 IIoT Framework Application -- 9.1 Industrial IoT Platforms (IIoT) -- 9.2 Conclusion -- References -- 9 Human-Robot Coordination and Collaboration in Industry 4.0 -- 1 Introduction -- 1.1 Robots at Workplace -- 1.2 Inclusion of Robot Workforce -- 1.3 Organizational Benefits of Including Robot Workforce -- 2 Literature Review -- 2.1 Table of Literature Review-Human-Robot Collaboration and Co-Ordination -- 3 Human-Robot Coordination and Collaboration -- 3.1 Drivers for Human-Robot Coordination and Collaboration -- 3.2 Barriers for Human-Robot Coordination and Collaboration -- 4 Human-Robot Coordination and Collaboration Towards Organization Performance -- 4.1 Organizational Performance -- 5 Framework for Human-Robot Coordination and Collaboration. 327 $a5.1 Framework for Human-Robot Coordination and Collaboration Towards Organization Performance -- 6 Implications -- 7 Conclusion and Future Research Scope -- References -- 10 Revolutionizing the Techno-Human Space in Human Resource Practices in Industry 4.0 to Usage in Society 5.0 -- 1 Introduction: What is Artificial Intelligence? -- 1.1 Literature Review -- 1.2 The AI Present Scenario -- 1.3 Racing to AI in Business -- 1.4 The HR World -- 1.5 Technology and HR -- 2 AI Ecosystem -- 2.1 Trends in the AI Ecosystem -- 2.2 AI Roadmap Development -- 2.3 Utilizing the AI Roadmap -- 2.4 Enhancing the HR Processes Using AI -- 2.5 Collaborative Intelligence in Recruitment Function: All About Estimations! -- 2.6 AI in Learning and Development Function of Human Resources Management -- 3 Collaborative Artificial Intelligence (CAI) Conceptual Background -- 3.1 Business and Collaborative Artificial Intelligence -- 3.2 Collaborative Artificial Intelligence in Business-Case 1 -- 3.3 Challenge Problems in CAI Scenarios -- 4 What is Society 5.0? -- 4.1 IOT-CAI-Smart Cities -- 4.2 IOT and Urban Knowledge -- 5 Conclusions -- References -- 11 An Architecture of Cyber-Physical System for Industry 4.0 -- 1 Introduction -- 1.1 Cyber-Physical Systems -- 1.2 Industry 4.0 -- 1.3 CPS Industry Compatibility with 4.0 -- 1.4 Characteristics -- 1.5 Inquiry on the Design of CPS -- 2 Literature Review -- 2.1 Implementation of CPS Technique -- 2.2 Case Study: Developing Own CPS -- 2.3 Case Study: KPIs Implementation -- 3 Information and Operational Technology -- 3.1 Operational Technology Support -- 3.2 Information Technology Support -- 4 Convergence of IT and OT in IIoT -- 4.1 IT and OT Are no Longer Separate Fields of Study -- 4.2 How Will IoT Embedded with IT and OT? -- 5 CPS Functions and Applications at a Glance -- 6 Electronic Platform -- 6.1 Necessity of an Electronic Platform. 327 $a6.2 Developing a Digital Business Technology Infrastructure. 410 0$aDisruptive Technologies and Digital Transformations for Society 5. 0 Series 700 $aKumar$b Avadhesh$01591950 701 $aSagar$b Shrddha$01591951 701 $aThangamuthu$b Poongodi$01591952 701 $aBalamurugan$b B$01591953 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910806192703321 996 $aDigital Transformation$93907833 997 $aUNINA