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This book discusses how Artificial Intelligence (AI) and Internet of Things (IoT) technologies can be utilized to optimize orchard production, management, and conservation to achieve sustainable agriculture development goals. To achieve sustainable development of the next generation of agriculture, it is essential to use modern technology tools to enhance orchard production efficiency, improve fruit quality, and promote intelligent orchard management. Recent developments in AI and IoT are featured in the book, providing solutions to primary orchard and horticultural challenges such as pest and disease management, weed control, and canopy management. As climate change continues to pose challenges to agriculture, highly affecting temperature fluctuations and changes in rainfall patterns, the book offers innovative solutions to enhance productivity, sustainability, and resilience in farming operations. By leveraging AI and IoT, the book seeks to empower the agriculture industry with the tools and strategies needed to adapt to changing environmental conditions and optimize resource use.
The intersection of AI, IoT, and agriculture is a critical focus in the current era, where food security, climate change, and sustainability are top global priorities. With the agricultural sector facing unprecedented challenges due to changing climate conditions, the integration of advanced technologies offers a pathway to resilience and sustainability. This book is timely as it addresses the urgent need for innovation in agriculture, providing actionable strategies to help farmers and agricultural managers navigate the complexities of modern farming while safeguarding the environment. This publication is particularly important now, as it contributes to the broader discourse on how technology can support sustainable development goals and ensure a stable food supply for the growing global population.
Sommario
Chapter 1. High-Throughput Field Plant Phenotyping of Horticultural Crops.- Chapter 2. Development of a Raspberry Pi-Based Automated Primary Root Length Measurement System for Tomato (Solanum lycopersicum).- Chapter 3. Development of Smart Drip Irrigation and Fungicide Application System for the Grapevine Management.- Chapter 4. Challenges and Opportunities for Developing Mini-plant Factory for Vegetable Cultivation in Household Urban Farming.- Chapter 5. Computational Intelligence in Climate-Adaptive Agriculture: Pathways to Resilient Food Systems.- Chapter 6. Agronomic Performance and Physiological Responses of Inbred Rice (Rc 512) Using Drone Seeding Technology.- Chapter 7. Deep Learning Strategies for Smart Agricultural Space - Diagnostics, Automation, and Quality Systems.- Chapter 8. Feature Selection Technique for Model Development.- Chapter 9. Development of Remote Autonomy of Multi-Cluster Agricultural Machinery Control System Using YOLO Deep Learning Algorithm and WebSocket Protocol.- Chapter 10. Development of Navigation System in Rural Roads using Deep Learning Algorithm for Autonomous Crawler Tractor.- Chapter 11. Development of Orchard Autonomous System using Zigbee Communication and Visual SLAM Technology.- Chapter 12. Instance Segmentation Based on Deep Learning Algorithm for Autonomous Navigation in Orchards.- Chapter 13. Intelligent Recognition of Orchard Environment: Instance Segmentation of Trees and Roads.- Chapter 14. Strategic Short Note: Prospect of Small-scale Agricultural Mechanization for Sustainable Agricultur
