ARTIFICIAL INTELLIGENCE AND METAVERSE THROUGH DATA ENGINEERING.

Two cutting-edge technologies that are completely changing the way humans interact with digital surroundings are artificial intelligence (AI) and the metaverse. Data engineering-driven AI is a major factor in determining how the metaverse experience is structured. To train AI models, data engineering entails gathering, processing, and evaluating enormous volumes of data. By providing a variety of datasets to AI algorithms, data engineering contributes to the creation of realistic virtual environments within the metaverse. This makes it possible for AI to create realistic settings, people, and interactions in the metaverse. Artificial intelligence (AI) can create individualized and immersive experiences in the metaverse by using data engineering to comprehend human behavior, preferences, and interactions. AI improves the realism and interactivity of the metaverse by continuously learning from data, giving the impression that it is a more organic extension of the real world. In conclusion, this book will highlight the intersection of data engineering, AI, and the metaverse fostering innovation in virtual experiences by obfuscating the distinctions between the real world and the virtual. The potential for developing dynamic, captivating, and customized virtual worlds that meet users’ various requirements and interests is enormous with this partnership. Contents Chapter 1 Implementing Fraud News Prediction Using Machine Learning Techniques Abstract 1. Introduction 2. Related Work 2.1. Random Forest in Fake News Detection 2.2. K-Nearest Neighbor 2.3. Logistic Regression 2.4. Usual Framework for Diagnosing Fake News 2.5. Summary and Motivation 3. Implementation and Analysis 3.1. Data Sets 3.2. Experimental Setup 3.3. Evaluation Matrics 3.4. Confusion Matrix 4. Results Conclusion References Chapter 2 Energy Sector and Its Safety Monitoring with Augmented Reality Abstract 1. Introduction 1.1. Origin of AR 1.2. Differences between AR and VR 1.3. Types of AR 1.3.1. Marker-Less AR 1.3.2. Marker-Based AR 1.4. Advantages of AR 1.5. Disadvantages of AR 1.5.1. Some Areas Where AR Is Applied 1.5.2. Health Sector 1.5.3. Education 1.5.4. Transport Sector 1.5.5. Business 1.5.6. Entertainment 1.5.7. Platforms For Developing AR Applications 1.6. AR Architecture 2. Related Work 2.1. Staff Training 2.1.1. Safety Enhancement 2.1.2. Networking 2.1.3. Facilitating Engineering Education 2.1.4. Enhancing Competitiveness 2.1.5. System Monitoring 2.1.6. Maintenance 3. Natural Gas Pipelines 3.1. Gas Pipeline Monitoring 3.2. Recent Pipeline Issues 3.3. Pipeline Leakage Detection 4. The Proposed Model 4.1. System Overview 4.2. Layout Overview 5. Limitations and Future Work 5.1. Limitations 5.2. Future Work Conclusion References Chapter 3 Blockchain Technology: Introduction, Applications and Challenges Abstract 1. Introduction 2. Blockchain and Its History and Types 3. Related Work 4. Applications and Challenges of Blockchain 5. Future Scope of Blockchain Technology Conclusion References Chapter 4 AI-Based Metaverse Cybersecurity Overview: Innovative Threats, Mitigation and Open Challenges Abstract 1. Introduction 2. Artificial Intelligence, Metaverse and Cybersecurity: An Overview 2.1. Natural Language Processing 2.2. Machine Vision 2.3. Block Chain 2.4. Networking 2.5. Digital Twin 2.6. Neural Interface 3. AI Based Threats 3.1. Password Guessing 3.2. Ransomware 3.3. Generative AI inspired Attacks 3.3.1. AI Inspired Cyber Threats In Metaverse 3.4. Generative AI Inspired Mitigation Solutions 3.5. Open Challenges Conclusion References Chapter 5 AI and Metaverse: Exploring the Intersection of Technology and Virtual Reality Abstract 1. Introduction 2. The History of the Metaverse Intertwined with Artificial Intelligence (AI) 3. Current Capabilities of AI and Metaverse 4. Future Potential of Metaverse with AI 5. Integration of AI in Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) 6. Role of AI in Enhancing Immersion and User Experiences in the Metaverse 7. AI Technologies in the Metaverse 8. Research Objectives 9. AI within Metaverse Applications 10. Intelligent Agents and Virtual Entities 10.1. AI-Powered Virtual Assistants within the Metaverse 10.2. Adaptive and Personalized Experiences through AI Algorithms 10.3. Realistic Simulations and AI-Driven Virtual Entities in Metaverse 11. Ethical Considerations and Potential Risks 11.1. Privacy and Data Security in the Metaverse 11.2. Algorithmic Bias and Fairness Challenges 11.3. Digital Identity, Authenticity, and Trust 11.3.1. How Digital Identity, Authenticity, and Trust Are Cultivated 11.4. Psychological and Emotional Well-Being of Metaverse Users 11.4.1. How to Support Psychological and Emotional Well-Being Conclusion References Chapter 6 Sustainable Biopolymers: Applications and Case Studies in Pharmaceuticals, Medical, and Food Industries Abstract 1. Introduction 1.1. Definition and Characteristics of Biopolymers 1.2. Importance of Sustainable Biopolymers in Various Industries 1.3. Environmental Benefits of Biopolymers 1.4. The Metaverse’s Potential Role in Sustainable Biopolymers 1.4.1. Objectives 1.5. Sustainable Biopolymers in the Pharmaceuticals Industry 1.5.1. Biodegradable Packaging for Pharmaceuticals 1.5.2. Controlled Drug Delivery Systems 1.5.3. Biopolymer-Based Drug Delivery Devices 1.5.4. Case Study: Utilization of Chitosan-Based Nanoparticles for Drug Delivery 1.6. Live Solutions and Future Prospects 1.7. Sustainable Biopolymers in the Medical Industry 1.7.1. Biocompatible and Biodegradable Medical Implants 1.7.2. Tissue Engineering Scaffolds 1.7.3. Wound Dressings and Bandages 1.7.4. Case Study: Biopolymer-based Scaffold for Bone Tissue Engineering 1.7.5. Live Solutions and Advancements in Biopolymer-Based Medical Devices 1.8. Sustainable Biopolymers in the Food Industry 1.8.1. Biodegradable Packaging for Food Products 1.8.2. Shelf-Life Extension Technologies 1.8.3. Case Study: Biopolymer-Based Antimicrobial Packaging for Fresh Produce 1.8.4. Live Solutions And Innovations in Biopolymer-Based Food Applications 1.9. Challenges and Future Directions 1.9.1. Regulatory Considerations for Sustainable Biopolymers 1.9.2. Technological Challenges and Research Opportunities Conclusion References Chapter 7 Society 5.0 Abstract 1. Introduction 1.1. Society 5.0 1.2. Advances in Different Domains of Society 5.0 Using Bleeding-Edge Technologies 1.2.1. Healthcare 1.2.2. Energy 1.2.3. Transportation 1.2.4. Education 1.2.5. Disaster Prevention 2. History and Concept of Society 5.0 2.1. Technological Advancements in Society 5.0 2.2. Societal Impact of Society 5.0 2.2.1. Positive Effects 2.2.2. Negative Effects 3. Policy and Governance for Society 5.0 4. Future Directions for Society 5.0 Conclusion References Chapter 8 DataVerse: Empowering Artificial Intelligence using Metaverse Abstract 1. Introduction 1.1. Metaverse the Future of Engineering 1.2. Metaverse for Machine Learning and AI 1.3. Metaverse and Cyber Security 1.3.1. Cybersecurity 1.3.2. Data Science 1.3.3. Metaverse 1.4. Emerging Technologies and Higher Education 1.4.1. Cybersecurity the Need of Digital World 1.4.2. Future Directions 2. AI and Metaverse 3. Applications of Metaverse 3.1. Healthcare 3.2. Manufacturing 3.3. Smart Cities 3.4. Gaming 3.5. Metaverse a Big Lead towards Data Science and Its Allied Areas 3.6. Meta Environment Conclusion References Chapter 9 Augmented Reality with the Mix of Artificial Intelligence and Data Engineering Abstract 1. Introduction to Augmented Reality 1.1. Examples of Augmented Reality 1.2. Importance and Applications of AR in Various Domains 1.3. Overview of AR Hardware and Software 1.3.1. AR Hardware 1.4. AR Software 2. Understanding Artificial Intelligence 2.1. Machine Learning, Deep Learning, and Neural Networks 2.1.1. Machine Learning (ML) 2.1.2. Deep Learning (DL) 2.1.3. Neural Networks 2.2. AI Applications in AR and Their Potential Impact 3. Integration of AI in Augmented Reality 3.1. Real-Time Object Recognition 3.2. Real-Time Object Tracking 3.3. Natural Language Processing (NLP) for AR applications 3.4. AI-Based Recommendation Systems in AR 4. Data Engineering for Augmented Reality and AI 4.1. Data Integration and Data Pipelines for AR and AI Applications 4.2. Data Quality, Security, and Privacy Considerations 5. Challenges and Future Trends Conclusion References Chapter 10 Data Integration with Artificial Intelligence Abstract 1. Introduction to AI and Blockchain Integration 2. Data Integration Challenges and Solutions 3. Knowledge Representation in Data Integration 3.1. No Knowledge in Data Integration 3.2. Partial Knowledge in Data Integration 3.3. AI-Driven Data Catalogs 4. Blockchain in Healthcare and Medical Data Sharing 4.1. Evolution of Blockchain in Healthcare 4.2. Regulatory Frameworks and Compliance 4.3. Technological Challenges 4.4. Interoperability in Healthcare 4.5. Stakeholder Acceptance 4.6. Future Directions 5. AI and Blockchain Integration in Metaverse 5.1. Overview of Metaverse 5.2. Fusing Blockchain and AI in Metaverse 5.3. Blockchain-Empowered Authentication 5.4. Types of Blockchain 5.5. Encryption and Ciphertext 5.6. Authentication and Security in Metaverse 5.7. Scalability Requirements 5.8. Context-Awareness in Metaverse 5.9. Noiseless Data in a Virtual World 5.10. Data Forensics in Metaverse 6. Case Study - Data Integration with AI 6.1. System Model for AI-Driven Data Integration 6.2. Performance Evaluation 6.3. Real-World Applications Conclusion References Chapter 11 The Future of Education: Writing Exams in the Metaverse at South African Universities Abstract 1. Introduction 2. Metaverse Literature Review in Education 2.1. Emergent Trends 3. Learnings for the South African Education System 3.1. Early adopters in South African Education Higher Education 4. Proposed Metaverse Examination Process Conclusion References About the Editors Index Blank Page