Agro-Cyber Intelligence: Harnessing AI and Biowaste for Sustainable Agriculture presents a comprehensive exploration of the transformation of agriculture through artificial intelligence, digital technologies, and sustainable resource management. The book addresses pressing global challenges such as climate change, resource depletion, and food security by integrating concepts of precision agriculture, cyber-physical systems, and circular economy approaches. It highlights the role of AI in enabling smart farming, predictive analytics, and automated decision-making, while also emphasizing the value of biowaste utilization for creating sustainable and economically viable agricultural solutions. Structured into thematic sections, the book covers foundational principles of digital agriculture, biowaste valorisation, AI-driven analytics, blockchain applications, and real-world case studies. It also discusses policy frameworks and socio-economic implications of Agri-tech innovations. Designed for students, researchers, professionals, and policymakers, this volume bridges theory and practice, promoting interdisciplinary collaboration and supporting the development of resilient, intelligent, and environmentally sustainable food systems for the future.

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.