Enriched Aviation Information Notice via Text Analysis and Geospatial Mapping
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Solution Overview
Problem
Aviation information notices, such as NOTAMs, are complex and difficult to read due to specialized language and spatial relationships, making it challenging for pilots and flight dispatchers to extract relevant information for flight planning, which can be time-consuming and prone to errors.
Innovation Solution
A computing device uses a text language analysis model to extract metadata from raw aviation information notices, mapping this information to geospatial data to generate enriched aviation information notices, providing a clearer and more graphical representation of airspace system components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If raw text aviation information notices are used, then complete information is provided, but the notices are complex and difficult to read
Solution Approach 1:
The patent segments the raw text notice into multiple components: extracts key metadata (facility type, status, effective time), separates geospatial information, and identifies affected areas. This segmentation transforms the monolithic text notice into structured, manageable data elements that are easier to process and understand while preserving complete information.
Solution Approach 2:
The patent extracts critical information from the raw text notice using text analysis models, pulling out metadata about facility status, location, and temporal effectiveness. This extraction separates the essential information from the complex text structure, making the notice easier to read while maintaining information completeness through structured representation.
2Reliability
If pilots review large numbers of complex notices, then comprehensive flight planning is achieved, but the process is time-consuming and prone to errors
Solution Approach 1:
The patent replaces manual mechanical review of text notices with an automated computing system that processes notices using text analysis models, extracts metadata, maps to geospatial data, and generates enriched representations. This substitution eliminates manual parsing errors and reduces review time while maintaining or improving flight planning accuracy through systematic processing.
Solution Approach 2:
The patent creates an enriched copy of the original notice that includes structured metadata, geospatial visualizations, and mapped information. This enriched representation serves as an enhanced copy that is easier to process at a glance, reducing the time needed to review multiple notices while maintaining comprehensive information for accurate flight planning.
3Measurement precision
If text language analysis models are used to extract metadata, then information extraction accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent introduces text analysis models as intermediary components that bridge the raw text notice and the structured metadata output. These models act as mediators that automatically interpret complex aviation terminology and extract accurate metadata, improving extraction precision while the modular architecture manages processing complexity through standardized interfaces.
Solution Approach 2:
The patent transforms the notice processing from text-based to structured data-based by changing the representation parameters. The raw text is converted into structured metadata fields, geospatial coordinates, and temporal parameters. This parameter transformation improves extraction accuracy while the systematic approach to data structuring manages processing complexity through consistent data formats.
Data Source
AI summary
A computing device is provided comprising a processor and a memory storing instructions executable by the processor. The instructions are executable to receive a raw aviation information notice that comprises text. A text language analysis model is used to extract metadata from the raw aviation information notice. The metadata comprises aviation operation information that describes a status of a component of an airspace system. Geospatial aviation data is received that corresponds to the component of the airspace system. The aviation operation information is mapped to the geospatial aviation data to thereby generate geometry data for the aviation operation information. The geometry data and the metadata are used to generate an enriched aviation information notice. The instructions are further executable to output the enriched aviation information notice.