Information Processing Device for Distribution-Based Data Extraction
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Solution Overview
Problem
Existing information processing devices struggle to extract data that captures the characteristics of the entire original data, including multiple feature quantities, leading to inefficiencies in data analysis.
Innovation Solution
An information processing device that acquires original data collected over a predetermined period and extracts data using a search process involving clustering, relative frequency distribution calculation, and error analysis to identify extracted data with equivalent analysis accuracy while reducing data volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compressed by extracting only vehicle speed data, then data volume is reduced, but characteristics of other feature quantities are lost
Solution Approach 1:
The patent changes the parameter of data selection from single-dimensional (vehicle speed only) to multi-dimensional (multiple feature quantities including rotational speed, acceleration, temperature). This allows comprehensive capture of data characteristics while reducing volume by selecting only representative time points across all feature dimensions.
Solution Approach 2:
The patent introduces a new dimension of selection criteria by considering multiple feature quantities simultaneously rather than relying solely on vehicle speed. This multi-dimensional approach enables better representation of original data characteristics with fewer data points.
2Measurement precision
If all original data is used for analysis, then analysis accuracy is maintained, but data processing time increases
Solution Approach 1:
The patent extracts only the most representative data points from the original dataset by identifying characteristic time points across multiple feature quantities. This extraction process maintains analysis accuracy by ensuring captured data points reflect overall data characteristics while dramatically reducing the total number of data points requiring processing.
Solution Approach 2:
Instead of processing all original data, the patent processes a partial subset of data points that are strategically selected to represent the entire dataset's characteristics. This partial action approach achieves equivalent analysis results with reduced computational burden.
3Ease of operation
If data is extracted using simple vehicle speed thresholds, then extraction process is simple, but data characteristics are not fully captured
Solution Approach 1:
The patent creates a universal extraction framework that handles multiple feature quantities (rotational speed, acceleration, temperature, etc.) using a unified approach. This multi-functional method systematically identifies characteristic time points across all feature dimensions, ensuring comprehensive data characteristic capture while maintaining process efficiency.
Data Source
AI summary
The processing device of the information processing device includes: a first step of calculating a relative frequency distribution of the original data; a second step of setting a plurality of time windows for cutting out data of a part of the period of the original data; a third step of cutting out data from the original data; a fourth step of calculating a relative frequency distribution in the extracted data; and a fifth step of calculating an error between the relative frequency distribution in the original data and the relative frequency distribution in the extracted data, and performs a search process of repeatedly executing the trial from the second step to the fifth step by changing the setting of the plurality of time windows.