Dynamic Collision Verification With Accuracy-Ranked Sensor Selection
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Solution Overview
Problem
Existing methods for verifying events using sensor data often result in inaccurate determinations, leading to resource wastage and safety concerns due to false positives or negatives.
Innovation Solution
A computing platform ranks sensor devices based on accuracy and compliance with geographic policies, collects and verifies data from multiple sensors using machine learning algorithms to generate accurate event outputs, and dispatches assistance when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If sensor data is used to determine whether an event occurred, then event detection capability is improved, but determination accuracy deteriorates due to false positives or negatives
Solution Approach 1:
The patent combines data from multiple sensor devices (first sensor device, second sensor device, third sensor device) to verify event determinations. By merging sensor data and cross-validating readings across multiple devices, the system improves determination accuracy while maintaining event detection capability, reducing false positives and negatives through consensus-based verification.
2Measurement precision
If multiple sensor devices are used for event verification, then determination accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the sensor network into hierarchical groups with designated leader sensor devices. Each group independently verifies events using its member sensors, and only group leaders communicate with the central platform. This segmentation reduces system complexity by organizing multiple sensors into manageable units while maintaining verification accuracy through distributed validation.
Solution Approach 2:
The patent introduces leader sensor devices as intermediaries between individual sensor devices and the central computing platform. Leaders aggregate and verify data from their group members before transmitting to the platform, reducing communication overhead and simplifying system architecture while preserving multi-sensor verification benefits.
3Measurement precision
If sensor devices transmit data to computing platform, then event verification accuracy is improved, but communication overhead and resource consumption increase
Solution Approach 1:
The patent divides the sensor network into groups with designated leaders who aggregate data from group members. Only leader sensor devices transmit verified event data to the central computing platform, significantly reducing communication overhead compared to having every sensor device communicate individually, while maintaining verification accuracy through group-based consensus.
Data Source
AI summary
Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification and sensor selection. A computing platform may determine accuracy for each of a plurality of sensor devices for each of a plurality of data types. For each of the data types, the computing platform may rank the plurality of sensor devices based on their corresponding accuracy. The computing platform may direct a first sensor device and a second sensor device to provide first and second source data respectively. These sensor devices may be the most accurate sources of data types corresponding to the first and second source data respectively. The computing platform may receive the first source data and the second source data. Based on the first source data and the second source data, the computing platform may generate an event output indicating whether a vehicle experienced an event.