Vehicle Data Verification Using Standardized Review Rules
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Solution Overview
Problem
Existing vehicle data verification tools struggle with reprocessing and visualizing vehicle data, have low readability, and lack standardized data verification standards, leading to inefficiencies and quality issues during software distribution and certification processes.
Innovation Solution
A vehicle data verification apparatus and method that includes a database and processor for decoding, verifying, and visualizing vehicle data, using predefined data frames, review rules, and failure diagnosis standards to automate the verification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual verification of vehicle data is performed by functional persons, then flexibility in reviewing important labels is maintained, but verification time increases significantly and complete review of all data variables becomes impractical
Solution Approach 1:
The system enables self-service verification by automatically comparing vehicle data against stored reference data and validation rules without requiring manual intervention for each data point. The automated verification process independently reviews all data variables, eliminating the time-consuming manual review while maintaining comprehensive coverage.
Solution Approach 2:
The patent replaces the mechanical manual verification process with an automated computer-based system. The processor automatically retrieves vehicle data, compares it with reference data, validates against predefined rules, and generates reports, substituting human manual operations with automated electronic processing.
2Reliability
If standardized data verification processes are implemented, then quality consistency and regulatory compliance improve, but adaptability to different verification scenarios decreases
Solution Approach 1:
The system provides dynamic adaptability through configurable validation rules and selective data parameter verification. Users can dynamically adjust verification parameters, select specific data variables to review, and modify validation criteria based on different scenarios while maintaining standardized processing architecture.
Solution Approach 2:
The verification system is designed with multi-functionality to handle various verification scenarios through a single unified platform. It can verify different types of vehicle data (engine, transmission, body, etc.), support multiple validation rules, and accommodate different reference data formats, providing universal applicability across diverse verification needs.
3Productivity
If automated decoding and verification of vehicle data is implemented, then verification efficiency and readability improve, but system complexity increases
Solution Approach 1:
The system segments the verification process into distinct modular functions: data retrieval, reference data storage, automated comparison, validation rule application, and report generation. This segmentation allows each function to be independently optimized and maintained, reducing overall system complexity while preserving high verification efficiency.
4Manufacturing precision
If comprehensive review of all vehicle data variables is performed, then verification completeness improves, but the ability of individual persons to review all data becomes impractical
Solution Approach 1:
The automated verification system performs self-service comprehensive review of all vehicle data variables without requiring human intervention. The system independently retrieves, compares, and validates every data point according to stored reference data and validation rules, achieving complete verification that would be impractical for individual persons to perform manually.
Data Source
AI summary
A vehicle data verification apparatus includes a database (DB) and a processor connected with the DB. The processor is configured to: import at least one vehicle data set; identify whether the at least one vehicle data set is stored in the DB; verify pieces of vehicle data in the at least one vehicle data set upon identifying that the at least one vehicle data set is stored in the DB; and export a result of the verification of the pieces of vehicle data.