Title: AI in Drone Spraying – Smart Agriculture Notes
Subtitle: Practical Guide for Agricultural Engineering & Technology Students
Author: MD.Jowel Rana
Department: Agricultural Engineering
University: Hajee Mohammad Danesh Science and Technology University, Dinajpur
Date: October 2025
Table of Contents:
1. Introduction to AI in Agriculture
2. Overview of Drone Technology in Farming
3. Applications of AI in Drone Spraying
4. Drone Spraying System: Design & Components
5. Working Principle of AI-based Drone Spraying
6. Comparative Table: Traditional Spraying vs AI-based Drone Spraying
7. AI Algorithms Used in Pest Detection
8. Image Processing and Machine Learning Steps
9. Precision Spraying and Mapping
10. Advantages of AI-based Drone Spraying
11. Limitations & Challenges
12. Case Studies (Bangladesh, India, USA, Kenya)
13. Integration with IoT and Smart Farming Systems
14. Future Scope of AI in Agriculture
15. Conclusion
16. References
1.Introduction to AI in Agriculture
Artificial Intelligence (AI) in agriculture refers to the use of machines, sensors, and algorithms
that can think, learn, and make decisions like humans to improve farming efficiency.
, AI enables farmers to monitor crops, detect pests, predict yields, and control spraying
operations automatically. It reduces labor cost, pesticide usage, and ensures sustainable food
production.
Example:
In a rice field, AI-powered drones detect pest-infested areas and spray only where necessary
— reducing pesticide by 40% and saving both cost and environment.
2.Overview of Drone Technology in Farming
Drones are unmanned aerial vehicles (UAVs) that can capture aerial images, monitor crops,
and spray pesticides or fertilizers.
Types of Agricultural Drones:
Type Use Battery Life Payload Field Size
Multirotor Precise spraying 30–40 mins 5–10 kg 1–3 ha
Fixed-Wing Long-range 1–2 hrs 10–15 kg 10–50 ha
mapping
Subtitle: Practical Guide for Agricultural Engineering & Technology Students
Author: MD.Jowel Rana
Department: Agricultural Engineering
University: Hajee Mohammad Danesh Science and Technology University, Dinajpur
Date: October 2025
Table of Contents:
1. Introduction to AI in Agriculture
2. Overview of Drone Technology in Farming
3. Applications of AI in Drone Spraying
4. Drone Spraying System: Design & Components
5. Working Principle of AI-based Drone Spraying
6. Comparative Table: Traditional Spraying vs AI-based Drone Spraying
7. AI Algorithms Used in Pest Detection
8. Image Processing and Machine Learning Steps
9. Precision Spraying and Mapping
10. Advantages of AI-based Drone Spraying
11. Limitations & Challenges
12. Case Studies (Bangladesh, India, USA, Kenya)
13. Integration with IoT and Smart Farming Systems
14. Future Scope of AI in Agriculture
15. Conclusion
16. References
1.Introduction to AI in Agriculture
Artificial Intelligence (AI) in agriculture refers to the use of machines, sensors, and algorithms
that can think, learn, and make decisions like humans to improve farming efficiency.
, AI enables farmers to monitor crops, detect pests, predict yields, and control spraying
operations automatically. It reduces labor cost, pesticide usage, and ensures sustainable food
production.
Example:
In a rice field, AI-powered drones detect pest-infested areas and spray only where necessary
— reducing pesticide by 40% and saving both cost and environment.
2.Overview of Drone Technology in Farming
Drones are unmanned aerial vehicles (UAVs) that can capture aerial images, monitor crops,
and spray pesticides or fertilizers.
Types of Agricultural Drones:
Type Use Battery Life Payload Field Size
Multirotor Precise spraying 30–40 mins 5–10 kg 1–3 ha
Fixed-Wing Long-range 1–2 hrs 10–15 kg 10–50 ha
mapping
