Biometric Clear Air Turbulence Detection With Real-Time Event Prediction
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Solution Overview
Problem
Existing methods for detecting clear air turbulence (CAT) are inaccurate and delayed due to reliance on weather forecasts and pilot reports, which lag current conditions and are subjective, leading to imprecise location estimation.
Innovation Solution
Utilizing real-time biometric data from vehicle occupants to detect CAT events, applying weight values based on occupant type, and generating predicted event locations for enhanced accuracy and real-time detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If weather forecast reports are used to detect CAT, then detection coverage is provided, but detection accuracy deteriorates due to 6-hour or greater lag time
Solution Approach 1:
The patent replaces traditional mechanical/weather-based detection systems with a biometric sensing system that monitors physiological responses (heart rate, respiration, galvanic skin response) of vehicle occupants in real-time, eliminating the 6-hour lag inherent in weather forecast reports
Solution Approach 2:
The patent introduces biometric data as an intermediary indicator that correlates with turbulence exposure, using physiological responses as a proxy measure to detect CAT events without directly measuring atmospheric conditions
2Loss of information
If pilot reports (PIREP) are used to document CAT encounters, then CAT information is captured, but real-time detection deteriorates due to manual initiation delays
Solution Approach 1:
The system enables automatic detection and reporting of CAT events through biometric monitoring, eliminating the need for manual pilot initiation and subjective assessment, with the system self-activating when turbulence is detected through physiological response changes
Solution Approach 2:
The patent implements continuous feedback loops where biometric sensors monitor occupants in real-time, immediately detecting physiological changes caused by turbulence and automatically triggering alerts without manual intervention delays
3Reliability
If onboard calculations are performed to detect CAT events, then CAT detection is achieved, but location precision deteriorates due to calculation latencies
Solution Approach 1:
The patent continuously monitors biometric data in real-time before, during, and after potential CAT events, capturing physiological responses at the moment of turbulence exposure to precisely timestamp and locate events without post-hoc calculation delays
Data Source
AI summary
Embodiments of the disclosure provide for clear air turbulence (CAT) detection. In the context of a method, the method includes receiving, from a vehicle, biometric data for at least one subject aboard the vehicle, wherein the biometric data meets a biometric abnormality threshold; applying a first weight value to a first subset of the biometric data determined to correspond to a passenger aboard the vehicle; applying a second weight value to a second subset of the biometric data determined to correspond to a crewmember aboard the vehicle, wherein the first weight value represents a greater impact value than the second weight value; determining the vehicle has encountered a monitored vehicle event representing CAT based at least in part on the first and second weight values; generating a predicted event location based on vehicle data associated with the vehicle; and providing the predicted event location to an additional vehicle.