UAV Aerial Imaging for Permanent Crop Yield Estimation
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Solution Overview
Problem
Current methods for estimating yield in permanent croplands are prone to errors, lack precision, and are time-consuming, as they rely on manual counting and visual inspections, which can lead to inaccurate financial reporting and reduced confidence in crop yield estimation.
Innovation Solution
The use of aerial imaging from sensors on vehicles, such as UAVs, to process images and classify plants into yield categories, enabling more accurate yield estimation by identifying individual plants and designating sentinel plants for yield calculation, which can be stored in a computer-readable medium.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual counting and visual inspection methods are used to estimate crop yield, then workers can directly observe and count plants, but the process becomes very time-consuming and prone to errors
Solution Approach 1:
The patent replaces manual mechanical counting and visual inspection with an automated aerial imaging system using UAVs equipped with sensors. The system captures images of the permanent cropland, processes them through computer vision algorithms to identify and count individual plants, and estimates yield without human intervention. This substitution eliminates the time-consuming nature of manual methods while maintaining or improving measurement precision through automated image analysis.
2Loss of information
If manual plant counting and inspection is performed, then detailed knowledge of plant health and quantity can be obtained, but the method lacks precision and is very time-consuming
Solution Approach 1:
The patent creates a digital copy of the physical cropland through aerial imaging. Sensors on the UAV capture high-resolution images that replicate the visual information of the entire field, allowing virtual analysis of plant quantity, health, and distribution. This digital copy enables precise measurement and detailed information extraction without the limitations of manual inspection, improving both information completeness and measurement precision simultaneously.
3Reliability
If traditional yield estimation methods using sentinel plants are used, then financial reporting can be performed, but confidence in crop yield estimation is reduced
Solution Approach 1:
The patent replaces the traditional sentinel plant method with an automated aerial imaging and image processing system. Instead of manually selecting and monitoring a few representative plants, the system captures and analyzes images of the entire cropland, providing comprehensive data that increases confidence in yield estimates. The automated nature of the system reduces methodological complexity while enhancing reliability through more complete and objective data collection.
Data Source
AI summary
One or more images are used to analyze permanent cropland. The images can be obtained from one or more sensors on an aerial vehicle including, but not limited to, UAVs. The analysis of the permanent cropland includes, but is not limited to, analyzing the plants growing in the permanent cropland or analyzing the permanent crops growing on the plants. In one embodiment, the analysis can include estimating a total yield of the permanent crops where the estimated permanent crop yield is more accurate than the estimated yield obtained using traditional methods.