Harvest Campaign Control Using Hierarchical Field Data Levels
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Solution Overview
Problem
Optimizing the control of an agricultural harvest campaign is complex due to the need for balancing machine-local and remote sensing field information, which existing methods fail to address effectively with low control technology complexity.
Innovation Solution
The method structures control application levels into rough, fine, and machine levels, using distributed control routines that process georeferenced remote sensing and live field information to generate processing sequences, harvesting process chains, and machine control data, ensuring consistent information availability and reducing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If remote sensing field information and machine-local field information are processed to optimize harvest campaign control, then the optimization quality improves, but the control technology complexity increases
Solution Approach 1:
The control system is segmented into three hierarchical application levels: coarse application level for overall harvest campaign planning, fine application level for field-specific optimization, and machine application level for real-time machine control. This segmentation allows complex optimization tasks to be distributed across multiple levels, reducing the complexity burden at any single level while maintaining comprehensive optimization quality.
Solution Approach 2:
The patent introduces a hierarchical dimension to the control architecture, transforming a potentially monolithic complex control problem into a multi-level structured system. By adding the temporal and spatial dimensions of hierarchical control levels, the system manages complexity through structured decomposition while preserving the ability to process both remote sensing and local field information for high-quality optimization.
2Reliability
If information is generated and made available at all application levels, then the optimization capability improves, but the information processing complexity increases
Solution Approach 1:
Information generation and processing are segmented across three application levels, with each level generating and utilizing specific types of information appropriate to its scope. The coarse level generates campaign-level information, the fine level generates field-level information, and the machine level generates operation-level information. This segmentation reduces information processing complexity at each level while ensuring comprehensive information availability for optimization.
Solution Approach 2:
Each application level processes information with local quality appropriate to its specific function and scope. Rather than processing all possible information types at all levels, each level focuses on generating and using the specific information most relevant to its optimization tasks, reducing overall processing complexity while maintaining comprehensive optimization capability.
3Loss of information
If remote sensing field information from external service providers is integrated, then the information completeness improves, but the system complexity increases
Solution Approach 1:
The hierarchical application level structure acts as an intermediary layer between external remote sensing data sources and the machine control system. Remote sensing information from external service providers is integrated at the coarse and fine application levels, which process and transform this information into actionable control parameters before passing them to the machine level. This intermediary structure improves information completeness while managing system complexity through structured information flow.
Data Source
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AI summary
The invention relates to a method for controlling an agricultural harvesting campaign in which predetermined harvesting actions are carried out on a field quota assigned to the harvesting campaign within a campaign period (tK) by several agricultural machines (1) of a machine fleet (2). It is proposed that the control of the harvesting campaign be carried out at different application levels, each generating data, that the generated data be made available to all application levels, and that the generated data include remote sensing data.