Vehicle Biometric Authorization With Multi-Threshold Confidence Checks
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Solution Overview
Problem
Biometric authorization systems in vehicles face challenges due to differences in sensor parameters and environmental conditions between interior and exterior sensors, leading to potential unauthorized access or denied access to authorized users.
Innovation Solution
A vehicle computer system that biometrically authorizes users by obtaining biometric data outside the vehicle and updating user data based on confidence scores exceeding different thresholds, ensuring accurate authorization while accounting for sensor differences and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single confidence threshold is used for biometric authorization, then the authorization process is simple and quick, but authorized users may be denied access or unauthorized users may gain access
Solution Approach 1:
The patent applies parameter changes by implementing multiple confidence thresholds (first confidence threshold and second confidence threshold) instead of a single threshold. The system compares the confidence score against these different thresholds to determine authorization, allowing for more nuanced decision-making that improves reliability while managing complexity through structured parameter differentiation.
Solution Approach 2:
The authorization process is segmented into multiple stages with different confidence threshold requirements. The system first checks against a first confidence threshold, and only if that fails does it proceed to check against a second confidence threshold. This segmentation allows the system to handle different authorization scenarios appropriately, improving overall reliability without requiring all users to undergo the most stringent verification.
2Reliability
If interior and exterior sensors use the same parameters, then the system is simpler to calibrate, but sensor differences cause authorization failures and security vulnerabilities
Solution Approach 1:
The patent applies local quality by recognizing that different sensors (interior vs. exterior) have different characteristics and environmental conditions. The system adjusts the confidence threshold based on which sensor captured the biometric data - using a first confidence threshold for exterior sensors and a second confidence threshold for interior sensors. This localized adaptation to sensor-specific conditions improves biometric data accuracy while managing calibration complexity through threshold adjustment rather than complex sensor reconfiguration.
Data Source
AI summary
Upon obtaining biometric data for a user of a structure while the user is outside the structure, user data for the user is updated based on a confidence score for the biometric data exceeding a first confidence threshold. Based on the confidence score for the biometric data not exceeding the first confidence threshold, instructions are provided to the user to provide updated biometric data. Then the user data is updated based on a confidence score for the updated biometric data exceeding a second confidence threshold. The second confidence threshold is greater than the first confidence threshold. Structure components are controlled based on the updated user data.