A Realtime Vegetation Stress Detection System on a Drone
Project number:
22026
Sponsor:
UA Department of Biosystems Engineering
Academic year:
2021-2022
Vegetation stress is a key indicator of crop health, which often is determined using manual field analysis. This project presents a real-time drone analysis as a cost- and time-saving alternative. The Crop Level of Stress Analysis with Visual Export (CLOSAVE) software system can detect and categorize the level of stress in vegetation leaves.
The design is split up into two elements. The primary element is the CLOSAVE software, which receives video from a drone as it flies over a crop and then uses machine learning algorithms to indicate areas of stress detected on the plant. A commercial off-the-shelf color camera captures the video, and the software is pre-trained to recognize vegetation stress indicators. The second element is a drone, custom-built entirely by the team, that uses parts tailored to the design requirements of the software.
The design is split up into two elements. The primary element is the CLOSAVE software, which receives video from a drone as it flies over a crop and then uses machine learning algorithms to indicate areas of stress detected on the plant. A commercial off-the-shelf color camera captures the video, and the software is pre-trained to recognize vegetation stress indicators. The second element is a drone, custom-built entirely by the team, that uses parts tailored to the design requirements of the software.
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