Aeronautical Data Conversion and Relevance Filtering Workflow
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Solution Overview
Problem
The existing systems face challenges in efficiently processing and analyzing aeronautical information data from multiple sources with different data structures and formats, leading to high complexity and resource inefficiency in data ingestion and comparison.
Innovation Solution
A system that converts data from various data structures into a common data structure, creates a relational database, identifies differences, and stores relevant data in a filtered database based on relevance metrics, facilitating automated data ingestion and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is published in different electronic formats for human readability, then ease of operation is improved, but device complexity increases due to multiple data structure conversions
Solution Approach 1:
The patent introduces an intermediary conversion system that transforms human-readable AIP data into machine-readable formats. This mediator handles the format conversion automatically, allowing the publishing system to maintain simple human-readable formats while the conversion layer manages the complexity of multiple data structure transformations.
Solution Approach 2:
The system changes the format parameter of AIP data from human-readable electronic formats to machine-readable structures through automated conversion. This parameter transformation enables machines to process the data efficiently while the original human-readable format is preserved for publication purposes.
2Manufacturing precision
If hundreds of human data analysts are employed to ingest and integrate AIP data, then manufacturing precision is improved, but loss of time increases due to manual processing
Solution Approach 1:
The patent replaces the mechanical system of manual data analysis with an automated computer-based system. The conversion toolset automatically ingests, validates, and transforms AIP data from multiple sources into machine-readable formats, eliminating the need for hundreds of human analysts while maintaining data accuracy through systematic validation rules.
Solution Approach 2:
The system enables self-service data processing where the automated conversion tools independently ingest, validate, and transform AIP data without human intervention. The validation rules and conversion processes operate autonomously, allowing the system to serve itself in processing large volumes of aeronautical information data.
3Productivity
If automated conversion to machine-readable formats is implemented, then productivity is improved, but device complexity increases due to validation and conversion infrastructure
Solution Approach 1:
The patent segments the data processing system into distinct modular components: ingestion modules for different AIP formats, validation rule engines, conversion toolsets for specific data types, and output generation modules. This segmentation allows each component to handle specific tasks independently, improving productivity while managing complexity through modularity and reusability.
Data Source
AI summary
An automated environment for aeronautical information services includes converting a first data set from a first data structure to a common data structure, automatically creating a common database based at least on the common data structure, converting a second data set from a second data structure to the common data structure, analyzing a difference between the first converted data set and the second converted data set to determine a relevance metric, and, if the relevance metric meets a relevance threshold, storing at least a portion of the second converted data set at a filtered database, the filtered database separate from the common database, wherein the portion is associated with the difference.