AI Debrief Reconstruction for Pilot Proficiency Assessment
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Solution Overview
Problem
Current computing and communication devices lack the ability to effectively reconstruct, analyze, and assess complex events and operations to determine the details of what happened, how it happened, and why, which hinders the identification of operator proficiency and potential improvements in training and event planning.
Innovation Solution
A method utilizing an application server to obtain and analyze pre-event and event execution information, generate reconstruction information, and compare it to determine operator proficiency, with artificial intelligence to provide real-time feedback and recommend remedial measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reconstruction and analysis of event data is performed, then operator proficiency assessment can be conducted, but the process becomes slow, tedious and laborious
Solution Approach 1:
The patent replaces manual mechanical analysis processes with automated computational systems. The server automatically reconstructs event timelines, analyzes operator actions, and generates proficiency assessments by processing event execution information and pre-event preparation information through algorithms, eliminating the need for manual review while maintaining assessment accuracy.
Solution Approach 2:
The system enables self-service proficiency assessment where the automated server performs the entire assessment workflow independently. The server collects data from multiple sources, reconstructs events, analyzes performance, and generates reports without requiring operator intervention, thereby speeding up the process while preserving measurement precision.
2Loss of information
If detailed event reconstruction is performed to determine what happened, how it happened, and why, then comprehensive proficiency assessment is achieved, but the complexity of data processing increases
Solution Approach 1:
The patent segments the complex data processing task into distinct modular components: data collection from multiple sources, event reconstruction module, analysis module, and reporting module. Each component handles specific aspects of the assessment, making the overall complex process manageable and systematic while preserving complete event details.
Solution Approach 2:
The server acts as an intermediary that automatically processes and integrates data from multiple disparate sources (event execution information, pre-event preparation information, environmental data). This intermediary system manages the complexity by standardizing data formats and processing workflows, reducing the burden on users while maintaining information completeness.
3Measurement precision
If multiple data sources and formats are integrated for comprehensive event analysis, then accurate proficiency assessment is achieved, but the difficulty of data fusion and parsing increases
Solution Approach 1:
The server is designed with universal data processing capabilities that can handle multiple data formats and sources through standardized interfaces. The system performs multiple functions including data collection, validation, transformation, and integration within a single platform, eliminating the need for separate processing systems for each data type and reducing integration complexity.
Solution Approach 2:
The system automatically transforms and standardizes parameters from different data sources into a unified format suitable for analysis. By changing the parameter representation and data structures during processing, the system facilitates seamless integration of diverse data types while maintaining the precision needed for accurate proficiency assessment.
Data Source
AI summary
A non-transitory computer readable medium stores instructions that, when executed by a processor, cause the processor to utilize artificial intelligence to update a mission for an aircraft flown by a pilot. The instructions include: receiving, from at least one storage device, pre-event preparation information that identifies a mission for the aircraft and includes historical information about the pilot; receiving, from an operator device, event execution information that describes how the aircraft is being flown; comparing the pre-event preparation information to the event execution information and the historical information about the pilot using artificial intelligence to determine a deviation from the mission indicating that the mission will likely not be successful; and updating the mission based on the deviation.