GPS Probe Data Quality Assessment and Real-Time Evaluation
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Solution Overview
Problem
Current methodologies lack the ability to effectively evaluate the relevance and value of bulk GPS probe data, determine the contribution of additional vendors, and perform real-time assessments for improving traffic analysis and monetization of raw probe data.
Innovation Solution
A system and method for assessing the quality of raw GPS probe data by cleaning, mapping, and smearing data to determine coverage value, comparing vendors, and performing real-time evaluations using historical profiles to project data quality and value, enabling a framework for monetization through an auction-based trading platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If bulk raw GPS probe data is purchased from multiple vendors, then the quantity of data points increases, but the relevance and quality of the data cannot be evaluated
Solution Approach 1:
The patent replaces manual or mechanical data quality assessment with an automated computational system that uses algorithms to evaluate GPS probe data quality. The system automatically analyzes data points, calculates quality metrics, and ranks vendors without human intervention, enabling precise quality evaluation of bulk data from multiple vendors.
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between raw GPS data and end-users. This system processes, analyzes, and scores data quality before presenting it to users, providing an intermediate layer that translates raw data into evaluated, actionable information about data relevance and quality.
2Area of stationary object
If additional vendor subscriptions are undertaken to improve traffic analysis, then data coverage increases, but the incremental value of each additional vendor cannot be determined
Solution Approach 1:
The patent applies partial action by evaluating and selecting only the necessary portion of vendor data that provides meaningful incremental value. Rather than blindly subscribing to all vendors, the system performs partial evaluation to identify which specific vendor contributions exceed a threshold of usefulness, avoiding excessive spending on marginally valuable data.
Solution Approach 2:
The patent changes the parameter of vendor evaluation from binary (subscribe/don't subscribe) to a continuous quality score that reflects incremental value. By transforming vendor data into comparable quality metrics and coverage measurements, the system enables precise determination of marginal value for each additional vendor subscription.
3Reliability
If real-time evaluation of probe data is implemented, then data quality prediction capability improves, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing quality metrics, coverage profiles, and vendor performance data before real-time evaluation is needed. This advance preparation creates lookup tables and historical baselines that enable fast real-time quality prediction without complex computational overhead during actual operation.
Solution Approach 2:
The patent uses copying by creating simplified models and representations of complex data quality characteristics. Instead of analyzing all raw GPS data in real-time, the system copies essential quality patterns into compressed formats and historical profiles, enabling rapid real-time evaluation through comparison with these pre-created models rather than full data re-analysis.
Data Source
AI summary
Quality assessment of probe data collected from GPS systems is performed by a system and method of determining a value of data points provided by different vendors of such data. Incoming raw probe data is initially analyzed for removal of extraneous data points, and is then mapped to roadway links and smoothed out. The resulting output is processed to determine the coverage value of data provided by a given vendor and enable a comparison between different vendors. Such a model of probe data processing also enables an evaluation of a contribution of further vendors of raw probe data to an existing dataset. Additionally, a real-time performance evaluation of continually-ingested probe data includes building historical and data count profiles, and generating output data represented by a number of data points for a specific distance within a geo-box representing a geographical area, to project a value of raw probe data for a next incremental time period.