Narayan Vyas, an academician at Vivekananda Global University, specializes in computer science, focusing on IoT and Mobile App Development. He has trained over 1000 students globally and published extensively in Scopus journals. An active IEEE member, his research interests include Remote Sensing, Machine Learning, and Computer Vision.
IoT and Remote Sensing Technologies for Precision Agriculture
Publisher: Apple Academic Press
Editors: Sartajvir Singh, Narayan Vyas, Dankan Dowda V
This book offers a comprehensive exploration of how advanced technologies are transforming modern agriculture. This book covers the integration of Internet of Things (IoT) and remote sensing technologies, focusing on their applications and benefits for crop monitoring and yield prediction. The chapters build a solid foundation, beginning with an introduction to the basics of IoT and remote sensing, and then delve into core principles of crop monitoring and yield prediction within precision agriculture. Additionally, it explores practical implementations, advanced imaging techniques, and the role of AI and drones in enhancing farming practices.
| Important Dates | |
|---|---|
| Abstract Submission Deadline | 15 August 2024 |
| Abstract Acceptance Notification | 15 September 2024 |
| Full Chapter Submission Deadline | 30 October 2024 |
| Chapter Acceptance Notification | 30 November 2024 |
| Projected Book Release Date | May 2025 |
| Important Guidelines | |
|---|---|
| Citation Style | American Chemical Society (ACS), 3rd Edition |
| Formatting | 11 pt Times Roman, 1.5 line spacing |
| Originality | Plagiarism Under 10%, 0% AI Generated Content |
| Headings |
|
Chapter 1: Introduction to IoT and Remote Sensing in Agriculture
Chapter 2: Fundamentals of Crop Monitoring and Yield Prediction for Precision Agriculture
Chapter 3: Integrating IoT Solutions for Smart Farming
Chapter 4: Remote Sensing Technologies for Precision Agriculture and Crop Yield Estimation
Chapter 5: Optical and Microwave Remote Sensing Applications in Crop Yield Prediction
Chapter 6: Detection of Soil Moisture Changes using Remote Sensing Dataset
Chapter 7: Multi-Spectral and Hyper-Spectral Imaging for Precise Change Detection
Chapter 8: Soil Health Monitoring Solutions using IoT, Remote Sensing, and Artificial Intelligence
Chapter 9: Harnessing the Potential of Drones in Agriculture: Enhancing Crop Surveillance
Chapter 10: Real-time Crop Monitoring Solutions with Advanced IoT Networks
Chapter 11: Pest and Disease Detection using Remote Sensing and IoT
Chapter 12: Climate and Weather Monitoring Systems for Agricultural Applications
Chapter 13: AI and Blockchain-Powered Smart Solutions for Precision Agriculture
Chapter 14: Challenges and Solutions for Sustainable Agriculture with Remote Sensing and IoT
Chapter 15: Future Trends in IoT and Remote Sensing Integration for Precision Agriculture
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