Information Processing Device for Multi-Feature Vehicle Data Extraction
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Solution Overview
Problem
Existing information processing devices fail to capture the characteristics of entire original data beyond vehicle speed, necessitating a solution that can extract data with multiple features while reducing data volume for efficient analysis.
Innovation Solution
An information processing device that performs a search process involving clustering, setting time windows, and calculating relative frequency distributions to extract data with errors less than a threshold, ensuring the extracted data captures the characteristics of the entire original data, including features like oil flow rate and shift frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is performed by extracting data based on single feature (vehicle speed), then data volume is reduced, but characteristics of entire original data including multiple features cannot be captured
Solution Approach 1:
The patent changes the parameters used for data extraction from a single parameter (vehicle speed) to multiple parameters including vehicle speed, acceleration, and other sensor data. This allows the system to maintain data representativeness across multiple dimensions while reducing overall data volume through selective extraction based on composite criteria.
Solution Approach 2:
The patent segments the original large dataset into multiple subsets based on different feature characteristics and time periods. By dividing the data into meaningful segments and selecting representative samples from each segment, the system preserves the diversity and characteristics of the entire dataset while achieving compression.
2Measurement precision
If entire original data is used for analysis, then accurate analysis results are obtained, but analysis time and processing load increase
Solution Approach 1:
The patent performs preliminary data extraction and segmentation before the actual analysis process. By pre-processing the data to identify and extract representative segments based on multiple features, the system prepares a reduced but representative dataset that maintains analysis accuracy while significantly reducing the time required for subsequent analysis operations.
3Quantity of substance
If data extraction focuses on specific conditions only, then data volume is reduced, but data representativeness of entire period is compromised
Solution Approach 1:
The patent creates a multi-functional data extraction system that simultaneously considers multiple features (vehicle speed, acceleration, various sensor readings) and multiple time periods. This universal approach ensures that the extracted data represents diverse operating conditions and maintains reliability across different scenarios while achieving data volume reduction.
Data Source
AI summary
A processing device of an information processing device performs a search process including: a first step of calculating a relative frequency distribution of the original data; a second step of setting a plurality of time windows for clipping data of a partial period of the original data; a third step of clipping 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 a trial from the second step to the fifth step being repeatedly performed by changing the setting of the time windows. In the second step, the time windows are set such that the ratio between the periods before and after the specific maintenance become equal to that in the entire original data.