Agricultural Work Unit Coordination Using Situation Pattern Recognition
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Solution Overview
Problem
The existing agricultural work system faces challenges in optimizing agricultural work flows due to the diversity of cooperation between various agricultural work units and unknown environmental conditions, particularly when using tractors with mounted implements, leading to unsatisfactory results in harvesting processes and other activities.
Innovation Solution
The implementation of a central pattern recognition system that identifies specific work situations and transmits meta-information to all functional units, allowing them to coordinate their actions based on the designation and description of the work situation, without providing explicit control instructions, and enabling parameter adjustments to optimize the cooperation of functional units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a decentralized control system with individual control devices is used for each functional unit, then the system structure is simple and easy to implement, but the coordination and optimization of agricultural work flows deteriorates due to diversity of cooperation and unknown environmental conditions
Solution Approach 1:
A central pattern recognition system is introduced as an intermediary between functional units and the control system. This mediator receives work situation information, identifies patterns, and generates coordinated control instructions for multiple functional units, resolving the contradiction by adding a coordinating layer without completely redesigning the decentralized structure
Solution Approach 2:
The control system is segmented into two functional parts: a central pattern recognition system for coordination and optimization, and individual control devices for local execution. This segmentation allows the system to maintain simple decentralized execution while adding centralized intelligence for workflow optimization
2Ease of operation
If individual functional units exchange data automatically based on stored rules, then the ease of operation is improved, but the reliability of work flow optimization deteriorates due to inability to handle diverse cooperation scenarios and environmental conditions
Solution Approach 1:
The pattern recognition system continuously receives work situation information from functional units, processes this feedback information, and adjusts control instructions dynamically. This feedback loop enables the system to adapt to diverse scenarios and environmental conditions while maintaining automatic operation
Solution Approach 2:
The system changes operational parameters dynamically based on pattern recognition results. The central system adjusts control instructions according to identified work situations, enabling reliable optimization across diverse scenarios without requiring manual intervention
Data Source
AI summary
An agricultural work system for optimizing agricultural work flows has at least one agricultural work unit and a plurality of functional units, each having a control device for controlling the respective functional unit based on a stored set of rules. The agricultural work system has a central pattern recognition system which stores at least one agricultural work situation as a situation pattern. Work situation-specific information is transferrable to the pattern recognition system which identifies a stored work situation and the associated situation pattern based on the obtained information and transmits meta-information (M) characterizing the identified work situation to the functional units. The pattern recognition system and/or the control devices coordinate the cooperation of those functional units which work together in the identified work situation based on the meta-information so that the control devices carry out corresponding parameter adjustments of the associated functional unit.