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Full Description
Precision agriculture is a next-generation farming management concept that optimizes resource use, productivity, quality, profitability, and sustainability by observing and responding to crop variability. Precision agriculture employs digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), 5G communication, cybersecurity, edge computing, cloud-native principles, and blockchain to ensure crops and soil receive exactly what they need for optimal health and productivity.
Artificial Intelligence for Precision Agriculture explores the latest developments in precision agriculture, detailing how AI contributes to its goals. The book discusses how precision agriculture solutions use IoT devices, data storage, AI analytics, connectivity, and cloud infrastructures to analyze factors such as soil type, terrain, weather, plant growth, and yield data. It also examines edge technologies—sensors, microchips, beacons, RFID tags, robots, drones, and actuators—that collect field data and transmit it to cloud-based AI platforms for analysis. The book shows how AI-driven insights guide actions in the field, such as crop rotation, optimal planting and harvesting times, and soil management, and help farmers apply the right amounts of water, fertilizers, and pesticides, reducing waste and environmental impact. Applications covered in the book include:
Drone-based high-resolution field mapping
Tracking crops
Crop yield assessments
Data collection for irrigation, fertilization, and crop management
Advanced weather monitoring
Equipment management
With chapters on AI model development, plant disease detection and remediation, sustainable farming techniques, data integration, AI-enabled data analytics, and knowledge visualization, this book is a comprehensive guide to technologies and applications in precision agriculture.
Contents
1. Machine Learning Algorithms and Applications 2. Introduction to Deep Learning 3. Role of AI in the Field of Precision Agriculture 4. How AI Contributes to Precision Agriculture 5. AI Model Generation Platforms 6. AI Deployment Models in Precision Agriculture 7. AI Model Deployment: Enhanced Rice Plant Disease Detection and Classification Besides Improved Spatial Pyramid with Enhanced YOLOv7 8. Sustainable Farming through AI-Enabled Precision Agriculture 9. The Significance of Data Integration and Ingestion in Enhancing Agricultural Operations: A Comprehensive Exploration 10. Revolutionizing Crop Yield Prediction in Agriculture: Harnessing Machine Learning and Environment Factors for Effective Solutions in the Face of Climate Change 11. AI in Optimization of Agricultural Output in Precision Agriculture 12. Data Analytics Methods for Precision Agriculture 13. Data Analytics Methods: A Hands-On Approach for Precision Agriculture 14. Smart Sensing Technologies and Data Analytics for Precision Agriculture 15. Knowledge Visualization Tools Relating to Agriculture
