Harvester Yield Data Calibration via Overlap Analysis
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Solution Overview
Problem
Existing yield monitor systems for agricultural data science applications face errors and deficiencies, particularly in multi-harvester scenarios where yield measurements need calibration and are affected by overlap, operational breaks, and outliers, limiting their value for industrial-scale analysis.
Innovation Solution
The method involves applying error detection algorithms, including overlap analysis, operational break analysis, outlier detection, and machine-to-machine calibration to process yield data, adjusting measurements to generate calibrated yield data usable across multiple platforms for agricultural decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If yield monitor data is collected from multiple harvesters, then the quantity of yield data increases, but measurement precision deteriorates due to machine-to-machine calibration errors
Solution Approach 1:
The patent introduces an intermediary calibration process that uses reference measurements and statistical methods to mediate between multiple harvesters with different measurement biases. A calibration factor is computed for each harvester based on overlapping harvest areas and reference yield data, serving as a mediator to standardize measurements across machines.
Solution Approach 2:
The patent changes the measurement parameters by applying harvester-specific calibration factors to adjust yield measurements. Each harvester's raw yield data is transformed using computed calibration parameters that account for machine-specific variations, thereby standardizing the measurements across the fleet.
2Measurement precision
If overlap analysis is performed to correct yield data, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent performs preliminary overlap analysis during the data collection phase, identifying and flagging overlapping harvest areas in advance. This preliminary action allows the main processing to focus only on correcting and integrating the already-identified overlap regions, reducing overall processing time.
Solution Approach 2:
The patent segments the harvest data by harvester, field, and overlap region, allowing parallel processing of different segments. Each segment can be processed independently for calibration and integration, significantly reducing total processing time through concurrent computation.
3Measurement precision
If machine-to-machine calibration is applied, then measurement precision improves, but device complexity increases
Solution Approach 1:
The calibration system is designed to be self-calibrating by automatically computing calibration factors from the harvest data itself. The system uses overlapping harvest areas and reference measurements to autonomously determine calibration parameters without requiring manual intervention or complex external calibration equipment.
Solution Approach 2:
The patent simplifies device complexity by transforming the calibration problem into parameter adjustment rather than hardware modification. Simple multiplicative calibration factors are applied to yield measurements, avoiding complex hardware changes while achieving measurement standardization.
Data Source
AI summary
A method for determining crop yield may include receiving yield data, associated respectively with a plurality of harvester machines. The method may further include determining a primary harvester machine, where the primary harvester machine is associated with a largest total harvested area of the plurality of total harvested areas. The method may also include determining a plurality of adjacent harvested areas associated, respectively, with each of the plurality of harvester machines, other than the primary harvester machine, and determining a secondary harvester machine, where the secondary harvester machine is associated with a largest adjacent harvested area of the plurality of adjacent harvested areas. The method may include adjusting a yield measurement associated with the secondary harvester machine using yield measurements associated with the primary harvester machine and generating calibrated yield data including the adjusted yield measurements.