Crop-Canopy UAV Imaging for Early Disease Detection
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Solution Overview
Problem
Current unmanned aerial vehicles (UAVs) for agricultural field management lack the necessary resolution and quality in imagery acquisition to effectively diagnose diseases, pests, and nutritional deficiencies, especially due to propeller downwash and entanglement issues in dense canopies.
Innovation Solution
The development of an unmanned aerial vehicle (UAV) equipped with a control and processing unit that allows it to fly within the crop canopy and acquire images from various positions, including below the vertical height of the crop and between rows, enabling early detection of diseases, pests, and nutritional deficiencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the UAV hovers stationary above the crop and lowers the camera into the crop canopy, then images can be acquired from within the canopy, but the propeller downwash generates significant leaf movement and the camera can get entangled in crowded canopies
Solution Approach 1:
The camera is extracted from the UAV body and mounted on an extendable arm that can be lowered into the canopy. This separates the imaging function from the propulsion system, allowing the camera to be positioned within the canopy while the UAV hovers above, eliminating propeller-induced leaf movement from the imaging area.
Solution Approach 2:
An extendable arm acts as an intermediary between the UAV and the crop canopy. This intermediate structure allows the camera to reach into the canopy for close-up imaging while maintaining a safe distance between the UAV's propellers and the delicate plant leaves, preventing both leaf movement and camera entanglement.
2Measurement precision
If the camera is lowered into the crop canopy to acquire images, then high resolution images can be obtained, but the process becomes time consuming
Solution Approach 1:
The UAV performs preliminary hovering and positioning above the canopy before deploying the camera. This preliminary action allows the system to establish the optimal imaging position and orientation in advance, so that when the camera is extended into the canopy, images can be captured immediately without repeated positioning adjustments, thereby maintaining high productivity.
Solution Approach 2:
The extendable camera arm provides dynamic positioning capability, allowing the camera to be rapidly extended and retracted as needed. This dynamic mechanism enables the system to quickly acquire multiple images from different positions within the canopy without the time-consuming process of physically moving the entire UAV, thus maintaining high field scouting speed while obtaining high-resolution images.
3Productivity
If the UAV flies above the canopy, then it can cover large areas quickly, but it cannot detect diseases, pests, or nutritional deficiencies that occur at the stem or underside of leaves
Solution Approach 1:
The imaging system transitions from a two-dimensional aerial view to a three-dimensional position within the canopy volume. By extending the camera into the canopy and enabling the UAV to fly at varying heights, the system accesses previously unreachable dimensions where stem and underside-of-leaf issues are visible, dramatically improving disease detection accuracy while maintaining efficient field coverage through rapid vertical positioning.
Data Source
AI summary
The present invention relates to an unmanned aerial vehicle (UAV) for agricultural field management. The UAV comprises a control and processing unit (20) and a camera (30). The control and processing unit is configured to control the UAV to fly to a location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crop. The control and processing unit is configured to control the camera to acquire at least one image relating to the crop at the location inside the canopy of the crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to analyse the at least one image to determine at least one disease, at least one pest and/or at least one nutritional deficiency.