Visual Flight Data Capture Neural Network
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Solution Overview
Problem
Current aircraft training methods face challenges in efficiently capturing and analyzing flight data from visual analysis of flight instruments without electrical connection, requiring significant human input and lacking automated comparison to flight maneuver standards.
Innovation Solution
A machine learning neural network system that captures flight data through visual analysis of aircraft instruments, compares it to standards, and provides visualization and analysis with minimal human input, using data capture and analysis neural networks trained for real-time operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video recording is used to document flight training sessions, then historical flight information can be captured, but it requires significant time to review and parse the video, and the video may not capture information from flight instruments
Solution Approach 1:
The patent replaces manual video review and parsing with an automated computer vision system that uses machine learning models to detect and extract flight instrument data directly from video feeds. The system automatically identifies instrument readings, flight maneuvers, and training events, eliminating the time-consuming manual analysis process while capturing comprehensive flight information.
Solution Approach 2:
The system enables self-service by automatically processing flight training videos without requiring instructor intervention for data extraction. The automated analysis pipeline independently captures flight parameters, compares them against standards, and generates training assessments, freeing instructors from manual video review tasks.
2Ease of operation
If instructors manually monitor and review flight training sessions, then real-time feedback can be provided, but the instructor must pay attention to multiple information sources including flight data and student actions, which divides attention
Solution Approach 1:
The patent introduces an automated analysis system as an intermediary between flight instruments and instructors. This system continuously monitors flight data, compares it against training standards, and highlights deviations or noteworthy events, allowing instructors to focus on student behavior and decision-making while the system handles detailed flight parameter analysis.
Solution Approach 2:
The system provides automated feedback by comparing real-time flight data against established standards and immediately identifying deviations. This continuous feedback loop supplements instructor observations with objective data analysis, ensuring comprehensive monitoring without dividing instructor attention.
3Adaptability or versatility
If complex simulators with gimbaled cockpits are used to simulate flight maneuvers, then realistic training can be provided, but they cannot simulate gross acceleration and will never entirely replace practical hands-on training
Solution Approach 1:
The patent uses computer vision to create digital copies of actual flight instrument readings and flight behavior. By analyzing video feeds from real aircraft or simulators, the system captures authentic flight data and reconstructs flight maneuvers digitally, preserving the characteristics of gross acceleration and other phenomena that physical simulators cannot replicate.
4Loss of information
If flight data is recorded using traditional flight data recorders and cockpit voice recorders, then flight history can be documented, but this information may not be available to support training and interfacing with these recorders is not trivial due to security and reliability requirements
Solution Approach 1:
The patent replaces direct interfacing with traditional flight data recorders with a computer vision-based system that captures flight information optically from instrument displays. This approach eliminates the complexity of electrical interfacing and security protocols associated with accessing protected flight data systems, while still achieving comprehensive flight history documentation.
Data Source
AI summary
Methods, apparatus, and system to acquire aircraft flight data through visual analysis of flight instruments with a data capture neural network, to compare aircraft flight data to a standard of a flight maneuver with a data analysis neural network with minimal or no human input, to output a visualization of aircraft flight data and or analysis of aircraft flight data, and to acquire aircraft flight data, programmatically analyze aircraft flight data, and provide aircraft training to a prospective aircraft pilot.