Covers digital technological intervention for precision agriculture for sustainable development. It delves into how modern technologies i.e., GPS, image processing, artificial intelligence, machine learning, Internet of Things, and deep learning are being used in agriculture to make it more farmer-friendly and economically profitable.
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.
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
Indias 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
Narendra Khatri, PhD, is Assistant Professor of Mechatronics at the Manipal Institute of Technology, India. He previously worked on a project for the Centre of Excellence for Digital Farming Solution for Enhancing Productivity Using Robots, Drones, and AGVs. He has published international journal articles and conference papers and is a peer reviewer for several journals.
Ajay Kumar Vyas, PhD, is Associate Professor of Information and Communication Technology at the Adani Institute of Infrastructure Engineering, India. He has published books and research articles and is a certified peer reviewer and an editorial board member of several journals.
Celestine Iwendi, PhD, is a visiting Professor with Coal City University, Nigeria, and Associate Professor with the School of Creative Technologies at the University of Bolton, UK. He is also a Fellow of the Higher Education Academy and the Institute of Management Consultants. He is a board member of IEEE, Sweden section.
Prasenjit Chatterjee, PhD, a Professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKV Institute of Engineering, India. A prolific author and editor, he has published many well-cited research papers and more than 35 books. Dr. Chatterjee is Editorin- Chief of the Journal of Decision Analytics and Intelligent Computing and an editor for several book series.
