Disruptive Technologies for Society 5.0: Exploration of New Ideas, Techniques, and Tools

Description

This book investigates how we as citizens of Society 5.0 borrow the disruptive technologies like Blockchain, IoT, cloud and software-defined networking from Industry 4.0, with its automation and digitization of manufacturing verticals, to change the way we think and act in cyberspace incorporated within everyday life. The technologies are explored in Non-IT sectors, their implementation challenges put on the table, and new directions of thought flagged off. Disruptive Technologies for Society 5.0: Exploration of New Ideas, Techniques, and Tools is a pathbreaking book on current research, with case studies to comprehend their importance, in technologies that disrupt the de facto. This book is intended for researchers and academicians and will enable them to explore new ideas, techniques, and tools. Cover Half Title Title Page Copyright Page Contents Preface Editor Biographies Section A: Disruptive Technologies: Introduction and Innovation 1. Blockchain and Internet of Things: An Amalgamation of Trending Techniques 1.1 Introduction 1.2 Literature Review 1.3 Blockchain 1.3.1 Types of Blockchain 1.3.1.1 Permission Seeking Blockchain 1.3.1.2 Permission Less Blockchain 1.3.2 The Structure of Blockchain Technology 1.3.3 Advantages of Blockchain Technology 1.3.4 Disadvantages of Blockchain Technology 1.4 Internet of Things (IoT) 1.4.1 Structure of IoT 1.5 Amalgamation of Blockchain Technology and IoT 1.6 Application Area of Blockchains in IoT 1.6.1 Agriculture Sector 1.6.2 Education Sector 1.6.3 Smart Homes and Smart Cities 1.6.4 Healthcare Sector 1.6.5 Hydrocarbon Industry 1.6.6 E-Business 1.6.7 Data Collection and Tracking 1.6.8 Finance 1.6.9 Tourism and Hospitality 1.7 Privacy and Security Related Issues 1.7.1 Threats 1.7.2 Attacks 1.7.3 Private Key Security 1.7.4 Fifty One% Vulnerability Attacks 1.7.5 Updation Issues 1.8 Limitations 1.9 Implications 1.10 Conclusion and Future Scope References 2. Software-Defined Networking: Evolution, Open Issues, and Challenges 2.1 Introduction 2.2 Software-Defined Network Architecture 2.3 Software-Defined Networks: Bottom-Up Scenario 2.3.1 Layer I: Network Infrastructure 2.3.2 Layer II: Southbound Interfaces 2.3.3 Layer III: Network Hypervisors 2.3.4 Layer IV: Controller (NOS) 2.3.5 Layer V: Northbound Interfaces 2.3.6 Layer VI: Language-Based Virtualization 2.3.7 Layer VII: Programming Language 2.3.8 Layer VIII: Network Application 2.4 SDN and Cloud Integration 2.5 Present Implementation and Challenges 2.6 SDN-Based Cloud Network 2.7 The Current State of SDN Implementation 2.8 Security Challenges in SDN 2.8.1 Switch-Level Security Challenges 2.8.2 Controller-Level Security Challenges 2.8.3 Channel-Level Security Challenges 2.9 SDN and Society 5.0 - Futuristic Approach 2.10 Conclusion and Future Scope References 3. Performance Enhancement in Cloud Computing Using Efficient Resource Scheduling 3.1 Introduction 3.2 Literature Survey 3.3 Proposed Research 3.4 Simulation Setup 3.5 Results Analysis 3.6 Conclusions 3.7 Limitation and Future Work References 4. Hyper-Personalized Recommendation Systems: A Systematic Literature Mapping 4.1 Introduction 4.1.1 Key Building Blocks of Hyper-Personalization 4.2 Literature Review 4.3 Research Method 4.3.1 Objectives 4.3.2 Methodology 4.4 Discussion 4.4.1 Personalization vs. Hyper-Personalization 4.4.2 Pitfalls of Traditional Approaches 4.4.3 Why Hyper-Personalization? 4.4.4 Hyper-Personalization Framework 4.5 Results 4.5.1 Classification on the Basis of Research Papers Used 4.5.2 Focus Areas 4.5.3 Experimental Analysis of Campaign Designing 4.6 Conclusion References 5. Evolutionary Computational Technique for Segmentation of Bilingual Roman & Gurmukhi Handwritten Script 5.1 Introduction 5.2 Literature Review 5.3 Framework for Segmentation Process of Bilingual Hrs 5.4 Word Level Segmentation 5.5 Pre-Processing 5.5.1 Duplicate Points Removal from Stroke Data (DPR) 5.5.2 Missing Points Identification from Input Stroke (MPI) 5.5.3 Normalization and Centering of Strokes (NCS) 5.6 Script Identification 5.7 Stroke Level Segmentation 5.8 Results and Discussion 5.9 Conclusion 5.10 Future Scope References 6. A Metric to Determine the Change Proneness of Software Classes Using GMDH Networks 6.1 Introduction 6.2 Literature Review 6.3 Research Methodology 6.4 Group Method of Data Handling Polynomial Networks (GMDH) 6.4.1 Structure of a GMDH Network 6.4.2 Algorithm 6.5 Empirical Data Collection 6.5.1 Independent and Dependent Variables 6.5.2 Machine Learning Algorithms Used 6.6 Evaluation Metrics Used 6.7 Results 6.7.1 Cross Validation Results 6.7.2 Results of Friedman Test 6.8 Class Change Factor (CCF) Metric 6.8.1 Definition of CCF Metric 6.8.2 Validating the CCF Metric 6.8.3 Application of CCF Metric 6.9 Conclusion and Future Work References Section B: Application of Disruptive Technology in Various Sectors 7. Application of IoT Technology in the Design and Construction of an Android Based Smart Home System 7.1 Introduction 7.2 Related Work 7.3 The System Model 7.4 Methodology and Logic Design 7.5 Packaging and Discussion 7.6 Conclusion 7.7 Limitations, Future Directions, and Recommendations References 8. Privacy-Preserved Access Control in E-Health Cloud-Based System 8.1 Introduction 8.1.1 Characteristics of Cloud Computing 8.1.2 Cloud Deployment Models 8.1.3 Cloud Service Models 8.2 E-Health Cloud Security and Privacy Issues 8.3 Recent Work in E-Health Privacy 8.4 Privacy Preservation E-Health Monitoring System 8.4.1 Broadcast Group-Key Management Scheme 8.4.2 Proposed Architecture 8.5 Experiment Results 8.6 Conclusion References 9. Eye Gaze Mouse Empowers People with Disabilities 9.1 Introduction 9.2 Background 9.3 Eye Gaze Mouse 9.3.1 Limitations of Previous Methods 9.3.1.1 Mouse Movement Using Pupil Detection 9.3.1.2 Additional Headgear 9.3.2 Working of Eye Gaze Mouse 9.3.2.1 Video Processing 9.3.2.2 Image Conversion to Grayscale 9.4 Face Detection Using Haar Cascade Classifier 9.4.1 Facial Landmarks Localization 9.4.2 Application Flow Detection 9.4.2.1 Eye-tracking to Give Direction for Mouse 9.4.3 Eyeball Tracking Left and Right as an Extra Input 9.4.4 Blink Detection 9.4.4.1 Eye Features Detection Processing Image to Find the White Part of the Eye 9.5 Results 9.6 Future Research Directions 9.7 Conclusion References 10. Strategies for Resource Allocation in Cloud Computing Environment 10.1 Introduction 10.1.1 Resource Allocation 10.1.2 Resource Allocation System 10.1.3 Significance of Resource Allocation System 10.1.4 Challenges of Resource Allocation 10.2 Literature Review 10.3 Strategies 10.3.1 Existing Strategies 10.3.2 Proposed Strategies for Admission Control and Resource Allocation 10.4 Analysis and Result 10.5 Conclusion and Future Scope References 11. Optimization Mechanism for Energy Management in Wireless Sensor Networks (WSN) Assisted IoT 11.1 Introduction 11.2 Literature Review 11.3 Methodology 11.4 Algorithm of Proposed Method 11.5 Experimental Results 11.6 Conclusion References 12. Intelligent Systems for IoT and Services Computing 12.1 Literature Survey 12.2 Introduction 12.3 Proposed Method 12.4 Three-Layer IoT Architecture and Its Components 12.4.1 Hardware Requirements 12.4.2 Software Requirements 12.5 Scope of the Sensor Networked Devices 12.5.1 Scope of the Wireless Things 12.5.2 IoT and Its Market Segments 12.5.3 Experimental Analysis of the scanning Method 12.6 The IoT Contains an Enormous Variety of Connected Objects 12.6.1 Tiny Stuff: Smart Dust Enormous Stuff: An Entire City 12.6.2 Digital Locks 12.6.3 Smart Buildings 12.6.4 Data Collection by Existing Process 12.7 Common Problems with Data 12.8 Working Methodology 12.9 A Bunch of Convolutional Neural Networks 12.10 Selection of Loss Function (Training) 12.11 IoT & Machine Learning Another Application for Urban Intelligence 12.11.1 Bringing Data-Driven Management to Complex, Fast-Paced Environments 12.12 Challenges 12.12.1 Solution 12.13 Key Benefits 12.14 Sample Use Cases for the Restaurant Industry 12.14.1 Food Quality Control 12.14.2 Automated Restaurant Management 12.14.3 Data Sharing to Drive Commercial Purchases 12.14.4 Distributed Marketplace for Commodities 12.14.5 Inventory Management 12.14.6 Queue Management 12.14.7 Smart Waste 12.14.8 More Use Cases 12.15 How It Works in Brief 12.15.1 RFID Tags 12.15.2 The Foundation for IoT 12.16 IoT Smart Public Transportation System 12.17 IoT Based Smart Electricity Distribution System for Industries and Domestic Usages 12.18 Remote Health Monitoring System for Fetal and Mother Health Monitoring 12.19 Smart, Safe and Clean Streets 12.20 IoT Based Healthcare Solution for Tracking Human Spine Movement 12.21 IoT Based Smart Parking System 12.22 IoT Based Assisting System for Miners to Prevent Accidents 12.23 IoT Based Disease Prevention System for Smart Healthcare 12.24 Intelligent Toll Collection System for Highways 12.25 Forecasting Potential Health Threats 12.26 Conclusion 12.27 Limitations/Future Work References 13. Framework for the Adoption of Healthcare 4.0 - An ISM Approach 13.1 Introduction 13.2 Literature Review 13.3 Research Methodology 13.4 Results and Discussions 13.5 ISM Model for Healthcare 4.0 Adoption 13.6 MICMAC Analysis 13.7 Policy Implication 13.8 Conclusion 13.9 Limitations and Future Direction Acknowledgement References Section C: Impact of Disruptive Technologies in Society 5.0 14. E-commerce Security for Preventing E-Transaction Frauds 14.1 Introduction 14.2 Related Research 14.3 Proposed Approach 14.4 Features of E-Commerce Website 14.5 Security Considerations for E-Transactions 14.6 Types of Biometric Security 14.6.1 Physiological 14.6.2 Behavioral 14.7 Techniques Used in E-Commerce for Security 14.8 Data Analysis 14.9 Limitations and Challenges 14.10 Conclusion and Future Scope References 15. Botnet Forensic Analytics for Investigation of Disruptive Botherders 15.1 Introduction 15.1.1 Problem Statement 15.1.2 Research Objective 15.2 Research Methodology 15.3 Related Work 15.3.1 Research Gap 15.4 Research Framework 15.5 Framework Deployment 15.5.1 Framework Phases 15.6 Data Description 15.7 Model Selection 15.8 Experiment and Result 15.8.1 Performance Analysis 15.9 Research Limitations 15.10 Conclusion and Future Scope References 16. Design of a Toolbox to Give One Stop Solution for Multidimensional Data Analysis 16.1 Introduction 16.2 Review of the Existing System 16.3 Design of the Toolbox 16.3.1 Conceptual Design of a Toolbox 16.3.2 Conceptual Design of a Query Generation Process 16.3.3 Generation of Multidimensional Report and Visualization 16.4 Statistical Analysis and Data Mining on Multidimensional Space 16.4.1 Statistical Algorithms 16.4.1.1 Single Series Algorithms Test for Random Fluctuation Time Series Statistics Anderson - Darling Test Runs Test 16.4.1.2 Two Series Algorithms Mann - Whitney U Test Two Dependent Population Testing Two Sample Comparison of Variance 16.4.1.3 Multiple Series Algorithms One Factor ANOVA Kruskal - Wallis Test 16.4.1.4 Matrix Algorithms Rank Conversion Transformations Pearson Correlation Matrix 16.4.2 Advanced Techniques 16.4.2.1 Regression Analysis 16.4.2.2 XY-Graph 16.4.2.3 Data Transformation 16.4.2.4 K-Means 16.5 Case study: Analyzing the Environment Using the Spatio-Temporal Data Generated by the Sensors 16.5.1 Motivation 16.5.2 Inputs and Workflow 16.5.3 Data Modelling 16.5.4 Multidimensional Analysis 16.5.5 Outcome of Case Study 16.6 Conclusion and Future Scope References 17. IoT Based Intelligent System for Home Automation 17.1 Introduction 17.1.1 History 17.1.2 Working of IoT 17.1.3 Importance of IoT 17.1.4 IoT Benefits to Organizations 17.1.5 Advantages and Disadvantages of IoT 17.1.6 Privacy and Security Issues 17.1.7 Major Components of IoT 17.1.8 Applications of IoT 17.2 Architecture 17.3 Literature Survey 17.4 Experimental Setup 17.5 Conclusion 17.6 Future Scope References 18. Digital Learning Acceptance during COVID-19: A Sustainable Development Perspective 18.1 Introduction 18.2 Problem Statement 18.3 Literature Review 18.4 Research Methodology 18.5 Findings 18.6 Discussion 18.7 Managerial Implication 18.8 Limitation 18.9 Future Research References 19. A Framework for Real-Time Accident Prevention using Deep Learning 19.1 Introduction 19.2 Drowsiness Detection 19.2.1 Ways to Detect Drowsiness 19.2.2 Related Work 19.3 Proposed Model 19.3.1 System Requirement 19.3.2 Proposed System Algorithm 19.3.3 Pre-Processing 19.3.4 Classification and Feature Extraction using CNN 19.4 Results 19.5 Conclusion and Future Scope References 20. Multi-Modality Medical Image Fusion Using SWT & Speckle Noise Reduction with Bidirectional Exact Pattern Matching Algorithm 20.1 Introduction 20.2 Medical Modalities 20.2.1 X-Ray 20.2.2 Ultrasound 20.2.3 Computed Tomography (CT) 20.2.4 Magnetic Resonance Imaging (MRI) 20.2.5 Positron Emission Tomography (PET) 20.2.6 Speckle Noise Based Model 20.2.6.1 Types of Speckle Noise Filter 20.2.6.1.1 Wiener Filter 20.2.6.1.2 Median Filter 20.3 Strategies of Image Fusion 20.3.1 Spatial Fusion Domain 20.3.1.1 Average Methodology 20.3.1.2 Principal Component Analysis (PCA) 20.3.1.3 Intensity Hue Saturation (IHS) 20.3.1.4 High Pass Filter (HPF) 20.3.1.5 Brovey Transforms (BT) 20.3.2 Transform Fusion of Domain 20.3.2.1 Discrete Wavelet Transform (DWT) 20.3.2.2 Methodology of Pyramids 20.3.2.3 Stationary Wavelet Transform (SWT) 20.4 Proposed Work 20.5 Result and Discussion 20.5.1 Average Pixel Intensity (API) 20.5.2 Standard Deviation (Sd) 20.5.3 Coefficient of Correlation (Cc) 20.5.4 Average Gradient (Agr) 20.5.5 Entropy (En) 20.6 Conclusion References Index