Dynamic Farm Field Task Planning for Harvest Optimization
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Solution Overview
Problem
Existing farm field management systems are not optimized to dynamically adjust task plans based on real-time harvest impeding factors such as diseases, insect pests, and weather conditions, leading to suboptimal income and cost management.
Innovation Solution
A farm field management apparatus that generates multiple task plan candidates by selecting harvest tasks, predicting harvest impeding factors, calculating income and cost based on crop quantity and unit price, and optimizing resource utilization, using a processor and storage system to dynamically adjust plans according to current farm field conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed task plan is set in advance, then the planning process is simple, but the plan cannot adapt to changing harvest impeding factors such as diseases, insect pests, and weather conditions
Solution Approach 1:
The task plan is transformed from a static fixed schedule to a dynamic adaptive plan. The system continuously monitors harvest impeding factors (diseases, insect pests, weather) and automatically adjusts task timings and resource allocations in real-time, allowing the plan to evolve with changing conditions while maintaining optimization goals.
Solution Approach 2:
The system implements feedback loops where monitored data on harvest impeding factors is fed back into the task plan generation process. This feedback mechanism enables the system to detect changes in disease presence, pest infestation levels, or weather conditions and automatically modify the task plan to address these changes, resolving the adaptability complexity contradiction.
2Productivity
If multiple task plan candidates are generated dynamically, then the optimization of income and cost is improved, but the computational complexity and time required increase
Solution Approach 1:
The task plan generation process is segmented into modular components: harvesting tasks, disease control tasks, pest control tasks, and resource allocation sub-plans. This segmentation allows the system to generate and evaluate multiple candidates more efficiently by processing independent modules in parallel, reducing overall computational time while maintaining comprehensive optimization.
Solution Approach 2:
The system varies key parameters such as harvest timing, resource allocation quantities, and task sequencing across multiple candidate plans. By systematically changing these parameters within realistic ranges, the system generates diverse optimized plans without requiring exhaustive search, thereby improving productivity while controlling generation time.
3Loss of energy
If resource utilization is optimized based on real-time data, then the cost management is improved, but the system complexity increases
Solution Approach 1:
The resource optimization module is designed as a multi-functional system that handles multiple objectives simultaneously: minimizing task costs, maximizing harvest income, and adapting to varying conditions. This universal approach consolidates multiple functions into a single integrated optimization process, improving cost management while avoiding the need for separate complex subsystems.
Solution Approach 2:
The system performs self-optimization by automatically analyzing real-time data on harvest impeding factors and adjusting resource allocation without requiring manual intervention. The optimization algorithm self-adjusts task timings and resource distribution based on monitored conditions, reducing the need for complex manual control mechanisms while achieving cost efficiency.
Data Source
AI summary
A farm field management apparatus: in generation of each task plan candidate, selects at least one task that includes harvest task, selects, a resource that is used to carry out each selected task, determines a task time within a predetermined period in which each selected task is carried out, includes the selected task, the selected resource, and the determined task time in each task plan candidate; obtains; information about a harvest impeding factor that is predicted for a harvest time of each task plan candidate; calculate an income from a harvest of each task plan candidate, based on a relevant piece of the harvest impeding factor information, and on the quantity and unit price of each crop; and calculates task cost of each task plan candidate based on a resource utilization period of the resource included in each task plan candidate, and on the utilization cost.