- ホーム
- > 洋書
- > 英文書
- > Nature / Ecology
Full Description
This new book delves into how modern technologies—i.e., global positioning systems (GPS), unmanned aerial vehicles (drones), image processing methods, artificial intelligence, machine learning, and deep learning—are being used to make agriculture more farmer-friendly and more economically profitable. The volume focuses on the use of smart sensors, actuators, and decision support systems to provide intelligent data about crop health and for monitoring for yield prediction, soil quality, nutrition requirement prediction, etc. The authors discuss robotic-based innovations in agriculture, soft computing methodologies for crop forecasting, machine learning techniques to classify and identify plant diseases, deep convolutional neural networks for recognizing nutrient deficiencies, and more.
Contents
PART I: AI IN AGRICULTURE 1. Review of Various Technologies Involved in Precision Farming Automation 2. State-of-the-Art Technologies for Crop Health Monitoring in Modern Precision Agriculture 3. Comprehensive Study of Artificial Intelligence Techniques for Early-Stage Disease Identification System in Plants 4. Understanding the Relationship between Normalized Difference Vegetation Index and Meteorological Attribute Using Clustering Algorithm 5. Agricultural Productivity Improvement: Role of AI and Yield Prediction Using Machine Learning PART II: ROBOTIC-BASED INNOVATIONS IN AGRICULTURE 6. Comprehensive Review of Agricultural Robotics: A Post-Covid Perspective of Advanced Robotics with Smart Farming 7. Autonomous Aerial Robot Application for Crop Survey and Mapping 8. Structural Design and Analysis of 6-DOF Cylindrical Robotic Manipulators for Automated Agriculture 9. Robot-Based Weed Identification and Control System 10. Design and Development of a Quadruped Robot for Precision Agriculture Applications 11. Design and Fabrication of a Solar-Powered Bluetooth-Controlled Multi-Purpose Agro Machine PART III: INTELLIGENT COMPUTING IN AGRICULTURE 12. Machine Learning and Deep Learning Methods for Yield Forecasting 13. Supervised Machine Learning for Crop Health Monitoring System 14. Analyzing the Effect of Climate Change on Crop Yield Over Time Using Machine Learning Techniques 15. Deep Learning Techniques for Crop Nutrient Deficiency Detection: A Comprehensive Survey 16. Plant Disease Detection Techniques: A Survey PART IV: IoT IN AGRICULTURE 17. Internet of Things Enabled Precision Agriculture for Sustainable Rural Development 18. Internet of Things: A Growing Trend in India's Agriculture and Linking Farmers to Modern Technology 19. IoT-Based Condition Monitoring System for Plantation 20. Smart Farming Based on IoT Edge Computing: Applying Machine Learning Models for Disease and Irrigation Water Requirement Prediction in Potato Crop Using Containerized Microservices 21. Smart Sensors for Soil Health Monitoring 22. An IoT-Aided Smart Agritech System for Crop Yield Optimization 23. FATEH: A Novel Framework for Internet of Things based Smart Agriculture Monitoring System
