Scenario Envelope Generation from Flight Log Data
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Solution Overview
Problem
Current simulation and game-based training methods are labor-intensive and time-consuming, leading to a shortage of realistic scenarios, as they often require lengthy collaborations between software engineers and instructional professionals, resulting in scenarios that do not reflect recent experiences or lessons learned due to delays.
Innovation Solution
A processor-based method for defining scenario events by identifying key events and decision points, generalizing these attributes, and connecting them into a continuous envelope to create a scenario envelope, allowing for the recreation of actual events with flexibility for trainee interaction, using data sources like flight logs to enhance training scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional collaboration between software engineers and instructional professionals is used to develop scenarios, then scenario quality and realism are improved, but development time and labor intensity increase significantly
Solution Approach 1:
The system automatically copies and adapts real-world flight data from flight logs to create training scenarios, eliminating the need for manual scenario authoring while preserving the authenticity and realism of actual flight events and decision points
Solution Approach 2:
The system enables self-service scenario generation by automatically processing flight log data into structured training scenarios without requiring extensive manual collaboration between engineers and instructional professionals, significantly reducing development time while maintaining scenario quality
2Adaptability or versatility
If traditional scenario authoring processes are used, then scenarios can be customized and reviewed, but the number of scenarios produced decreases and reuse increases
Solution Approach 1:
The system creates a universal scenario generation platform that processes various flight log data formats into multiple training scenarios simultaneously, enabling one system to serve multiple training purposes and generate diverse scenarios from the same data source
Solution Approach 2:
The system generates multiple scenario variations by changing parameters such as decision point configurations, event sequences, and training objectives from the same underlying flight data, allowing customization without requiring separate authoring processes for each scenario
3Manufacturing precision
If manual scenario development is used, then scenarios can be carefully constructed, but delays prevent scenarios from reflecting recent experience or lessons learned
Solution Approach 1:
The system performs preliminary processing of flight log data into structured scenario formats in advance, so that when training needs arise, scenarios can be quickly generated and updated without lengthy manual construction processes, maintaining both quality and timeliness
Data Source
AI summary
Processor based systems and methods of defining a scenario event comprising the steps of identifying an event having an event attribute and generalizing the event attribute to define a generalized event whereby the generalized event is the scenario event. In some embodiments, the steps further comprise identifying a first and second event, generalizing a first and second event attribute to define a first and second generalized event and connecting the first and second generalized event in a continuous envelope to create a scenario envelope. Processor based systems and methods of monitoring an activity comprising the steps of monitoring an activity having an activity attribute and comparing the activity attribute to an event envelope to determine a status of the activity relative to the event envelope.