Work Machine Allocation System Using Terrain History Analysis
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Solution Overview
Problem
Existing systems face challenges in efficiently determining the optimal number and ratio of work machines for tasks, particularly in landscaping and similar industries, where terrain and worker skill variations complicate work machine allocation.
Innovation Solution
An information processing apparatus that utilizes a processor, memory, input, communication, and storage units to analyze work machine information, terrain data, and work history to determine the appropriate number and ratio of work machines for a given area by referencing similar terrain areas and optimizing team formation based on idling times and skill levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If work machines are allocated for work in landscaping industry, then work can be performed, but it is difficult to efficiently perform work depending on the number and/or ratio of allocated work machines
Solution Approach 1:
The system performs preliminary analysis of terrain information and work history data before allocating work machines. By pre-processing terrain data and historical performance information, the system determines optimal machine numbers and ratios in advance, avoiding inefficient allocations during actual work execution.
Solution Approach 2:
The system utilizes work history information containing idle time data from previous operations to continuously improve machine allocation decisions. By feeding back historical performance data into the allocation algorithm, the system learns from past inefficiencies and optimizes future allocations to reduce idle time and improve productivity.
2Productivity
If terrain information and work history are analyzed to determine optimal work machine allocation, then work efficiency improves, but processing complexity increases
Solution Approach 1:
The system creates simplified representations of complex terrain information by extracting key features and characteristics from detailed terrain data. Instead of processing all raw terrain information, the system uses copied essential attributes (such as terrain type, slope categories, and accessibility features) to make allocation decisions, reducing processing complexity while maintaining accuracy.
Solution Approach 2:
The system transforms complex terrain information into standardized parameters and categories that are easier to process. By converting continuous terrain data into discrete categories (such as terrain difficulty levels, machine suitability ratings, and work area classifications), the system simplifies the analysis process while preserving the essential information needed for optimal allocation.
Data Source
Figure 1
Figure 2A~2B
Figure 2C
AI summary
An information processing apparatus includes an obtaining unit for obtaining a work history of work performed by a plurality of types of work machines; and a determination unit for determining a number or ratio of work machines that perform work in an area to be subjected to work, based on the work history.