Agricultural Implement Row Unit State Data Processing
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Solution Overview
Problem
Agricultural implement operators face challenges in reviewing and modifying planting parameters in real-time to account for spatial variations in the field, making it difficult to ensure optimal planting operations.
Innovation Solution
A computer-implemented method that processes data from agricultural implements to calculate and determine state data for each row unit, using default or user configuration settings, to generate real-time state maps and alerts for operators, allowing for immediate corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If detailed planting data is collected and reviewed in real-time, then planting operation quality can be improved, but the complexity of data review and parameter modification increases
Solution Approach 1:
The patent segments the field into multiple zones based on spatial variations in planting parameters. Each zone is analyzed independently, allowing operators to focus on specific areas with issues rather than reviewing entire field data at once. This segmentation reduces the cognitive load and complexity of data review while maintaining high planting operation quality through targeted interventions.
Solution Approach 2:
The system introduces an automated data processing intermediary that collects, analyzes, and interprets planting data automatically. This intermediary processes raw planting data, identifies deviations from target parameters, and presents processed insights to operators. By placing this intermediary between data collection and operator review, the system reduces the complexity of direct data review while preserving the ability to achieve high planting quality through informed decisions.
2Reliability
If operators review planting data in real-time, then spatial variations can be addressed, but the time required to review and modify parameters increases
Solution Approach 1:
The system performs preliminary analysis of planting data automatically as data is collected, identifying potential issues and zones requiring attention before operators need to review the data. By pre-processing the data and highlighting areas of concern, the system reduces the time operators need to spend reviewing data while ensuring spatial variations are properly addressed through proactive identification of problems.
Solution Approach 2:
The system implements real-time feedback mechanisms that continuously monitor planting parameters and immediately notify operators of deviations from target values. This feedback loop provides timely information about spatial variations without requiring operators to manually review all data, reducing review time while maintaining reliable detection and management of spatial variations through automated monitoring and alerting.
3Loss of information
If comprehensive planting data is collected for the entire field, then complete coverage information is obtained, but the difficulty to understand and modify appropriate parameters increases
Solution Approach 1:
The patent applies local quality by providing different levels of data detail to different operators or for different purposes. The system maintains comprehensive coverage data for complete information but presents processed, zone-specific summaries to operators based on their needs and the identified issues. This allows the system to retain complete coverage information while reducing parameter understanding difficulty by presenting only relevant, processed data at appropriate locations in the interface.
Solution Approach 2:
The system creates processed copies of the comprehensive planting data that are easier to understand and interpret. Instead of presenting raw comprehensive data directly to operators, the system generates simplified representations, summaries, and visualizations that maintain the essential information about coverage while reducing the complexity of understanding and modifying parameters. These processed copies serve as intermediaries between comprehensive data collection and operator decision-making.
Data Source
AI summary
Described herein are systems and methods for determining state data for agricultural parameters during agricultural applications and providing spatial state maps. In one embodiment, a computer implemented method comprises obtaining as applied data of an agricultural implement as the agricultural implement passes through a field for an agricultural application. The computer implement method also includes processing the as applied data to calculate data for a parameter of the agricultural application and determining state data (e.g., quality indicator state) for each row unit based on the data for the parameter and at least one of default configuration settings or user configuration settings for the quality indicator state.