Predictive Residue Map for Uniform Agricultural Spreading
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Solution Overview
Problem
Agricultural harvesters face challenges in uniformly spreading residue across fields, leading to issues like nutrient concentration, pest habitats, and herbicide inefficacy due to non-uniform residue coverage, which affects crop development and machine performance.
Innovation Solution
The use of in-situ sensors and predictive mapping to generate a predictive residue map that predicts residue characteristics based on vegetative index, moisture, and topographic maps, enabling automated control of residue spreading for uniform coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional residue spreading methods are used, then the harvesting operation can be completed, but the residue distribution becomes non-uniform causing nutrient concentration, pest habitats, and herbicide inefficacy
Solution Approach 1:
The system performs preliminary mapping of field characteristics (vegetative index, moisture, topography) before the harvesting operation to predict residue distribution patterns. This advance knowledge allows the control system to pre-calculate optimal residue spreading strategies and adjust machine settings in real-time to achieve uniform distribution, preventing the harmful effects of non-uniform residue coverage.
Solution Approach 2:
The system continuously monitors actual residue distribution during harvesting using sensors and compares it against the predictive model. This feedback loop allows real-time adjustments to be made to the residue spreading process, correcting deviations from uniform distribution and ensuring that the desired outcome is achieved despite variations in field conditions or machine performance.
2Manufacturing precision
If automated control systems are implemented to improve residue spreading, then uniform residue coverage can be achieved, but the device complexity increases
Solution Approach 1:
The control system integrates multiple functions into a single automated platform: predictive mapping, real-time monitoring, control algorithm execution, and machine setting adjustment. By combining these functions into one multi-functional system rather than separate devices, the complexity is managed more efficiently while still achieving precise residue spreading control.
Solution Approach 2:
The system uses the harvester's own operational data and field characteristics to automatically adjust residue spreading parameters without requiring external intervention. The automated control system self-regulates based on predictive models and real-time feedback, reducing the need for manual operation and simplifying the user interface while maintaining high precision.
Data Source
AI summary
One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.