Autonomous Machine Recommendation Using Time, Region, and Cost
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Solution Overview
Problem
Existing systems for recommending autonomous working machines do not adequately account for variations in machine performance, leading to potential mismatches between user needs and machine capabilities, particularly in terms of working time, work region, and cost.
Innovation Solution
An information output device and method that acquires user requests and working machine performance data to provide tailored recommendations for autonomous working machines, considering factors like working time, work region, and cost, and can suggest suitable models or combinations of machines to meet user requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only work region condition is used for recommendation, then the recommendation process is simple, but the recommendation accuracy does not satisfy user requests
Solution Approach 1:
The patent changes the parameters used for recommendation from only work region conditions to multiple parameters including working time, cost, and machine performance specifications. This allows the recommendation system to provide more accurate results that satisfy user requests while maintaining a manageable process complexity.
2Measurement precision
If multiple machine performance parameters are considered, then the recommendation accuracy improves, but the information processing complexity increases
Solution Approach 1:
The patent segments the information processing by dividing it into distinct modules: acquiring work region conditions, acquiring machine performance specifications, determining recommended models based on multiple parameters, and outputting recommendations. This segmentation manages the complexity of processing multiple parameters while maintaining high recommendation accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where the determination unit uses both work region conditions and machine performance specifications to iteratively refine recommendations, ensuring accurate matching while systematically managing the complexity of multi-parameter processing.
3Loss of time
If autonomous working machines are selected without considering working time and cost, then the selection process is quick, but the user satisfaction decreases
Solution Approach 1:
The patent incorporates working time and cost as key parameters in the recommendation determination process. By considering these additional parameters alongside machine performance specifications, the system provides recommendations that better align with user constraints and preferences, thereby increasing user satisfaction while maintaining efficient selection timing.
Data Source
AI summary
An information output device includes a first acquisition unit that acquires request information that is a request of a user, a second acquisition unit that acquires working machine information related to performance of an autonomous working machine and set for each type of the autonomous working machine, and an output unit that outputs recommendation information satisfying the request of the user, based on the request information and each piece of the working machine information. The request information includes information about a working time during which the autonomous working machine works, information about a work region in which the autonomous working machine works, and information about a cost for using the autonomous working machine, and the recommendation information includes information about a model of the autonomous working machine to be recommended to the user for acquisition.