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Real-time recognition of spraying area for UAV sprayers using a deep learning approach
Shahbaz Khan1,2, Muhammad Tufail1,2, Muhammad Tahir Khan1,2
1Department of Mechatronics Engineering, University of Engineering & Technology, Peshawar, Pakistan.
Plos One
|April 1, 2021
Summary
This study developed a deep learning system for Unmanned Aerial Vehicle (UAV) sprayers to accurately identify agricultural spraying areas in real-time. This technology enhances precision agriculture by minimizing environmental impact and operator exposure to agrochemicals.
Area of Science:
- Agricultural Science
- Robotics
- Computer Vision
Background:
- Conventional agrochemical application methods pose environmental and health risks.
- Unmanned Aerial Vehicles (UAVs) offer a safer and more precise alternative for agricultural spraying.
- Accurate real-time recognition of spraying areas is crucial for effective UAV-based applications.
Purpose of the Study:
- To develop an accurate, real-time recognition system for identifying spraying areas using UAV-mounted cameras.
- To enhance the precision and safety of agricultural spraying operations.
- To reduce environmental contamination and operator exposure associated with traditional agrochemical application.
Main Methods:
- A two-step target recognition system was designed utilizing deep learning algorithms.
- Image data was collected from a UAV operating over coriander cropland.
- A classifier was trained to accurately distinguish spraying areas within the agricultural landscape.
Main Results:
- The developed deep learning system achieved a high average F1 score of 0.955.
- The classifier demonstrated a rapid average computation time of 3.68 ms for recognition.
- The system proved effective in real-time identification of spraying zones.
Conclusions:
- The deep learning-based recognition system is highly accurate and efficient for UAV-based sprayers.
- This technology enables precise, real-time application of agrochemicals, optimizing crop management.
- The system contributes to sustainable agriculture by reducing chemical overuse and environmental impact.
