Adaptive Residue Detection for Real-Time Implement Control
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Solution Overview
Problem
Agricultural operations often result in residue coverage that is difficult to manage, as existing technologies lack effective methods for accurately detecting residue coverage and adjusting implement operations to maintain desired levels, leading to inefficiencies and potential environmental issues like erosion.
Innovation Solution
A system and method that utilize environmental and image data to select appropriate image processing methods for detecting residue coverage, generating control signals to adjust agricultural implements such as tillage tools, allowing for real-time adjustments in residue management based on detected residue levels and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fixed image processing methods are used for residue detection, then the system structure is simple, but the measurement precision of residue coverage is insufficient under varying environmental conditions
Solution Approach 1:
The patent implements dynamic image processing by selecting different processing methods based on real-time environmental conditions. The system transitions from static fixed algorithms to dynamic adaptive processing, where the controller chooses appropriate image processing methods according to detected environmental factors such as lighting conditions and weather, thereby maintaining high measurement precision across varying conditions.
Solution Approach 2:
The system changes processing parameters based on environmental conditions. Different image processing methods are selected by the controller according to environmental data, effectively changing the processing parameters to match conditions. This allows the system to maintain high residue coverage detection accuracy whether conditions are dry/wet, sunny/overcast, or involve different residue types.
2Productivity
If real-time residue detection and implement control is implemented, then the productivity and environmental protection are improved, but the device complexity increases
Solution Approach 1:
The controller serves multiple functions: it detects environmental conditions, selects appropriate image processing methods, calculates residue coverage, and generates implement control signals. This multi-functionality consolidates what would otherwise require separate systems into a single controller, improving productivity while managing device complexity through functional integration.
Solution Approach 2:
The system implements closed-loop feedback by continuously detecting residue coverage, comparing it to desired levels, and automatically adjusting implement operations accordingly. This real-time feedback mechanism enables the system to maintain optimal residue coverage dynamically, improving both productivity and environmental protection through automated control.
3Measurement precision
If environmental factors are considered in image processing selection, then the measurement precision is improved, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary action by pre-establishing the relationship between environmental conditions and appropriate image processing methods. The controller is programmed with knowledge of which processing methods work best under specific conditions, allowing it to quickly select the appropriate method without extensive real-time analysis, thus maintaining both accuracy and processing speed.
Data Source
AI summary
A residue detection and implement control system and method are disclosed for an agricultural implement. The system includes a source of environment data and image data of an imaged area of a crop field containing residue. The system includes a data store containing a plurality of image processing methods and at least one controller that processes the image data according to one or more image processing instruction sets. The controller selects one or more of the image processing methods based on the environment data, and processes the image data using the selected image processing instruction(s) to determine a value corresponding to residue coverage in the imaged area of the field. The controller adjusts the configuration of the agricultural implement to respond to the amount and type of residue detected.