• Chapter 1. Agri-Tech Evolution: Bridging Binary Code and Cultivation.
• Chapter 2. AI-Driven Transformation of Future Farming.
• Chapter 3. Role of Artificial Intelligence in Crop and Soil Intelligence.
• Chapter 4. Smart Soil and Crop Health Monitoring: A Disruptive IoT-AI Framework for Sustainable Precision Farming.
• Chapter 5. Real-Time Mango Ripeness Prediction via YOLOv8 Object Detection and Swin Transformer Models.
• Chapter 6. A Strategic Roadmap for Machine Learning Integration in Global Agronomic Systems.
• Chapter 7. Precision Agronomic Optimization Integrating IoT Edge Computing and Circular Bioeconomy.
• Chapter 8. Integrating Life Cycle Assessment and Machine Learning for Biowaste-based Products.
• Chapter 9. Leveraging SDOH for Disease Prediction using LightGBM, Bagging Ensemble, and Elastic-Net Logistic Regression.
• Chapter 10. Biowastes in Agriculture: Sources, Challenges and Opportunities.
• Chapter 11. Farm Biowaste into Profits: Making Waste Part of Farming in a Climate and Sustainable Bioeconomy.
• Chapter 12. Implementation of Technical Systems in the Circular Economy in Agriculture.
• Chapter 13. Vermicomposting for Circular Agriculture in Kanpur Dehat: A Sustainable Model for Biowaste Management.
• Chapter 14. A Case Study in the Textile Sector for Circular Economy as a Pathway to Sustainability.
• Chapter 15. Optimized System Architecture for IoT-Based Fitness Tracking: Real-Time Exercise Recognition Using Arduino and Edge AI.
• Chapter 16. Securing Smart Agriculture Technologies: Analyzing Cyber Security Threats and Risk Mitigation Strategies.
• Chapter 17. Novel Framework Using Artificial Intelligence and Machine Learning for Cybersecurity and Risk Management in Smart Agritech Systems.
• Chapter 18. Cybersecurity and Risk Management in Smart Agritech Systems.
• Chapter 19. Transforming Agri-Food Traceability and Biowaste Transparency with Blockchain.
• Chapter 20. Blockchain-Enabled Traceability Systems for Biowaste Management in Smart Agriculture: A Cyber-Physical Approach.