Field Region Definition from GPS Pass Data for In-Cab Analysis
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Solution Overview
Problem
Existing methods for defining field regions in agricultural data analysis are cumbersome and inaccurate, particularly when performed in the cab of a machine, lacking manual dexterity and recall of pass details.
Innovation Solution
Agricultural intelligence computer systems utilize GPS data from planters or sprayers to automatically define field regions based on pass data, allowing growers to create and edit field regions directly from the cab, enhancing accuracy and convenience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If freehand drawing tools are used to define field regions, then the operation can be performed on touchscreen displays, but the accuracy and precision of region boundaries deteriorate due to lack of manual dexterity in cab conditions
Solution Approach 1:
The system performs preliminary actions by automatically generating pass data and storing it before the user needs to define field regions. The pass data containing GPS coordinates and equipment trajectory information is captured during field operations and pre-processed into selectable pass segments, eliminating the need for manual freehand drawing and ensuring accurate region boundaries are established before analysis begins.
Solution Approach 2:
The system creates a digital copy of the actual equipment passes through GPS tracking data. Instead of manually drawing new boundaries, the system reproduces the exact paths taken by agricultural equipment during field operations, allowing users to select from pre-captured pass data that accurately reflects actual field work patterns and equipment movement.
2Device complexity
If manual freehand drawing is used to define field regions, then no additional equipment data is required, but the time and effort to accurately define regions increases significantly
Solution Approach 1:
The system performs preliminary data collection and processing during field operations. GPS coordinates, equipment trajectory, and pass information are automatically captured and stored in advance, so when it comes time to define field regions for analysis, users can immediately select from pre-processed pass data without spending additional time on manual boundary drawing or data collection.
Solution Approach 2:
The system serves itself by automatically capturing pass data during equipment operation without requiring additional manual intervention. The GPS tracking and data logging functions operate autonomously during field work, and the system automatically processes this data into selectable pass segments, eliminating the need for separate manual region definition steps.
3Measurement precision
If equipment pass data is automatically captured and stored, then field regions can be precisely defined based on actual equipment movement, but the data management complexity and storage requirements increase
Solution Approach 1:
The system segments the continuous pass data into discrete, selectable pass segments corresponding to individual field passes. Each pass is divided into manageable units with clear start and end points, allowing users to selectively define field regions by choosing specific pass segments. This segmentation organizes the large volume of GPS data into structured, easily manageable segments that can be independently selected and combined.
Solution Approach 2:
The system performs preliminary processing of raw GPS data into organized pass segments with metadata including start/end coordinates, timestamps, and equipment information. This pre-processing structures the data before user interaction, reducing the complexity of data management during region definition by presenting pre-organized, ready-to-use pass segments rather than raw coordinate streams.
Data Source
AI summary
Systems and methods define field regions within agricultural fields. An example computer-implemented method includes identifying a field, retrieving data for the identified field, and displaying a graphical display including the identified field and at least some of the retrieved data. The method also includes receiving, via the graphical display, an input to create a field region within the identified field based on passes of an agricultural apparatus in the identified field and retrieving pass data for the passes of the agricultural apparatus in the field. The method further includes displaying, on the graphical display, the pass data, defining the field region based on the pass data, so that a boundary of the field region corresponds to a start point and an end point of each of the passes of the agricultural apparatus, and displaying, on the graphical display, field performance data constrained to the field region.