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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.

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IoT and Remote Sensing Technologies for Precision Agriculture

IoT and Remote Sensing Technologies for Precision Agriculture

Publisher: Apple Academic Press

Editors: Sartajvir Singh, Narayan Vyas, Dankan Dowda G

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 Deadline15 August 2024
Abstract Acceptance Notification15 September 2024
Full Chapter Submission Deadline30 October 2024
Chapter Acceptance Notification30 November 2024
Projected Book Release DateMay 2025
Important Guidelines
Citation StyleAPA (7th Edition)
Formatting11 pt Times Roman, 1.5 line spacing
OriginalityPlagiarism Under 10%, 0% AI Generated Content
Headings
  • Heading 1: ALL BOLD CAPS
  • Heading 2: Bold Title Case
  • Heading 3: Bold Italic Title Case
  • Heading 4: Bold Italic Sentence case
  • Heading 5: Light Italic Sentence case
  • Paragraphs: Should be Numbered (1.1, 1.1.1, etc.)
  • 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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