Digital Twins and ESG

Chapter 1: Digital Twins: Driving Innovation Through Virtual Optimization – A Systematic Review

• • 1.1 Introduction
• • 1.2 Literature Review
• • 1.3 Applications and Use Cases
• • 1.4 Challenges and Limitations
• • 1.5 Future Trends and Research Directions
• • 1.6 Conclusion

Chapter 2: Core Principles and Applications of Digital Twins

• • 2.1 Introduction
• • 2.2 History and Evolution of Digital Twins
• • 2.3 Key Components of Digital Twins
• • 2.4 Types of Digital Twins
• • 2.5 Digital Twin Architecture
• • 2.6 Interaction between Physical and Digital Components
• • 2.7 Data Flow and Management
• • 2.8 Digital Twin Frameworks
• • 2.9 Role of Cloud Computing in Digital Twins
• • 2.10 Data Collection and Integration

Chapter 3: ESG 2.0: Evolving Foundations and Strategies

• • 3.1 Introduction to ESG and Its Evolution
• • 3.2 Scope
• • 3.3 From ESG 1.0 to ESG 2.0 Evolution
• • 3.4 Key Drivers and Trends Influencing ESG 2.0
• • 3.5 The Core Areas of ESG 2.0
• • 3.6 Conclusion

Chapter 4: Fundamentals of Digital Twins

• • 4.1 Introduction
• • 4.2 Evolution of Digital Twins
• • 4.3 Types of Digital Twins
• • 4.4 Classification of DT Based on Their Applications
• • 4.5 Steps Involved in Creating DT
• • 4.6 Characteristics of DT
• • 4.7 Advantages of DT
• • 4.8 Disadvantages of DT
• • 4.9 Key Enablers
• • 4.10 Applications of DT

Chapter 5: Machine Learning Lending a Hand to ESG: A Case Study on CO 2 Emissions

• • 5.1 Introduction
• • 5.2 Evolution of ESG
• • 5.3 Applications of ESG
• • 5.4 Challenges and Limitations of ESG
• • 5.5 Case Study
• • 5.6 Conclusion

Chapter 6: A Comprehensive Review on Digital Initiatives Fostering Improvements in Solar PV Systems

• • 6.1 Introduction
• • 6.2 Digital Model Applications in the Field of Solar PV Industry
• • 6.3 Digital Twin of Solar PV Plant
• • 6.4 Conclusion

Chapter 7: The Convergence of AI, ML, and Digital Twins in Shaping the Future of ESG

• • 7.1 Introduction
• • 7.2 Understanding Digital Twins
• • 7.3 AI and ML Technologies
• • 7.4 Integration of AI, ML, and Digital Twins
• • 7.5 Impact on ESG Metrics and Reporting
• • 7.6 Innovations and Future Directions
• • 7.7 Challenges and Considerations
• • 7.8 Conclusion

Chapter 8: A Roadmap for Sustainable Industry: Merging ESG, Digital Twin, and Circular Economy Practices

• • 8.1 Introduction
• • 8.2 Environmental, Social and Governance (ESG)
• • 8.3 Digital Twin Technology
• • 8.4 Circular Economy
• • 8.5 Life Cycle Assessment (LCA)
• • 8.6 Conclusion

Chapter 9: Waste Biomass to Bioenergy with Regulatory Framework for a Sustainable Economy

• • 9.1 Introduction
• • 9.2 Biowaste Sources
• • 9.3 Bioengineering Techniques for Biowaste Conversion to Bioenergy
• • 9.4 Social Impact of Bioenergy Products
• • 9.5 Bio-Circular Economy for Sustainable Bioenergy Production
• • 9.6 Future Perspective

Chapter 10: An Automated System to Identify and Detect the Faults in Bottle Cap Production and Visual Inspection Using Raspberry Pi

• • 10.1 Introduction
• • 10.2 Existing Techniques and Proposed Approach
• • 10.3 Design and Implementation
• • 10.4 System Validation
• • 10.5 Conclusion

Chapter 11: DDoS Detection Using Semi-Supervised Machine Learning Algorithms

• • 11.1 Introduction
• • 11.2 Existing System
• • 11.3 Proposed System
• • 11.4 Conclusion

Chapter 12: Enhanced Encryption and Digital Signature Scheme Utilizing EC-Based Encryption and Multi-Chaotic Pseudo Random Generation

• • 12.1 Introduction
• • 12.2 Literature Review
• • 12.3 Proposed Methodology
• • 12.4 Simulation Results
• • 12.5 Conclusion and Future Scope

Chapter 13: Utilization of Waste for Production of Nanomaterials: An Industry 4.0 Approach of Waste to Wealth

• • 13.1 Introduction
• • 13.2 Critical Review
• • 13.3 Conclusions, Recommendations, Future Perspectives

Chapter 14: Factors Affecting Sanitation Behavior Among Rural Communities in Low and Middle-Income Countries: A Critical Review

• • 14.1 Introduction
• • 14.2 Research Methodology
• • 14.3 Literature Review
• • 14.4 Recommendations and Conclusion

Chapter 15: Assessing the Comparison of Environmental and Social Governance (ESG) Performance of Tourism Companies Worldwide

• • 15.1 Introduction
• • 15.2 Methodology
• • 15.3 Literature Discussion
• • 15.4 Secondary Data and Discussion
• • 15.5 Conclusion and Recommendation

Chapter 16: Ion Beam Induced PMMA-Based Corrosion-Resistant Hydrophobic Coating on a Metal Substrate

• • 16.1 Introduction
• • 16.2 Experimental
• • 16.3 Results and Discussion
• • 16.4 Conclusion