Collision Analysis Platform With Telematics False-Output Filtering
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Solution Overview
Problem
Existing systems for determining collisions using sensor data often result in false positive and false negative outcomes, leading to unnecessary resource allocation and conservation issues.
Innovation Solution
A computing platform applies machine learning algorithms to sensor data, utilizing geo-spatial and telematics filters to verify collision determinations, including analysis of angular velocity, barometric data, and user confirmation, to reduce false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If machine learning algorithms are applied to sensor data for collision determination, then automation extent is improved, but measurement precision deteriorates due to false positives and false negatives
Solution Approach 1:
The system implements feedback by comparing the initial collision determination against multiple additional data sources (geo-spatial location, telematics data, angular velocity patterns, barometric pressure changes) and iteratively refining the collision determination. This multi-layered feedback mechanism allows the system to correct false positives and false negatives while maintaining high automation, directly resolving the contradiction between automation extent and measurement precision.
Solution Approach 2:
The patent introduces intermediary verification layers between the initial sensor-based collision detection and the final collision determination. These intermediaries include geo-spatial filters that check location context, telematics data that provide vehicle operational context, and angular velocity analysis that distinguishes collision patterns from normal driving maneuvers. These intermediaries act as mediators that filter out false determinations while preserving true collisions.
2Measurement precision
If multiple verification filters are applied to reduce false positives, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The verification system is segmented into distinct, modular filters that operate independently: geo-spatial location filtering, telematics data analysis, angular velocity pattern recognition, and barometric pressure change detection. Each filter processes a specific aspect of the data and contributes independently to the final determination. This segmentation reduces overall system complexity by breaking down the complex verification task into manageable, specialized components.
Solution Approach 2:
The system performs preliminary actions by pre-establishing thresholds and criteria for each verification filter before actual collision detection occurs. Geo-spatial databases are pre-populated with location information, telematics parameters are pre-configured with normal operating ranges, and angular velocity thresholds are pre-determined based on historical data. This preliminary preparation reduces real-time processing complexity while maintaining high measurement precision.
Data Source
AI summary
Aspects of the disclosure relate to computing platforms that utilize machine learning to reduce false positive/negative collision output generation. A computing platform may apply machine learning algorithms on received data to generate a collision output. In response to generating the collision output indicating a collision, the computing platform may identify a data collection location. If the data collection location is within a predetermined radius of a false positive collection location, the computing platform may modify the collision output to indicate a non-collision. If the data collection location is not within the predetermined radius, the computing platform may compute a score using telematics data and compare the score to a predetermined threshold. If the score does not exceed the predetermined threshold, the computing platform may modify the collision output to indicate a non-collision. If the score exceeds the predetermined threshold, the computing platform may affirm the collision output indicating a collision.