AI Aeronautical Indicators for NOTAM Impact Prioritization

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Solution Overview

Problem

Pilots face a significant challenge in sorting through thousands of NOTAM messages daily, leading to increased cognitive load and the risk of overlooking important information due to the rapid increase in irrelevant messages, which can impact flight safety.

Innovation Solution

An electronic system on board the aircraft uses an artificial intelligence algorithm to calculate and display aeronautical indicators, such as energy consumption, delay, passenger disruption, crew disruption, environmental disruption, and ecological impact, based on the free text field of NOTAM, SNOWTAM, and ASHTAM messages, providing a more precise assessment of their flight impact.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If the number of NOTAM messages is increased to provide more comprehensive information, then the completeness of aeronautical information is improved, but the pilot's cognitive load increases and the risk of overlooking important messages increases

Engineering Contradiction:

Improvecompleteness of aeronautical informationVSAvoidrisk of overlooking important messages

Core Design Contradiction:

Loss of informationVSReliability

Solution Approach 1:

The patent extracts and highlights only the most critical information from NOTAM messages using natural language processing and machine learning algorithms. The system identifies and presents only the essential elements that directly impact flight operations, filtering out redundant or less important information to reduce cognitive load while maintaining completeness of actionable information.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces an intermediary system consisting of AI-based processing tools that act between the NOTAM messages and the pilot's decision-making process. This intermediary automatically analyzes, prioritizes, and presents information in a condensed format, serving as a bridge that reduces the information processing burden on the pilot while maintaining information completeness.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If more NOTAM messages are processed to improve information completeness, then the accuracy of flight safety assessment is improved, but the time required for information processing increases

Engineering Contradiction:

Improveaccuracy of flight safety assessmentVSAvoidtime required for information processing

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by having the machine learning system pre-analyze and pre-rank NOTAM messages before they reach the pilot. The system continuously processes incoming messages, identifies critical safety-related information in advance, and pre-presents it in a prioritized format, so that when the pilot receives the information, the most important items are already ready for immediate review, reducing real-time processing time while maintaining assessment accuracy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mechanical manual reading and analysis process with an automated electronic system using natural language processing and machine learning algorithms. This substitution allows for rapid processing of large volumes of NOTAM messages with high accuracy, eliminating the time-consuming manual review process while maintaining or improving the accuracy of flight safety assessments.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Ease of operation

If manual sorting of NOTAM messages is performed to reduce cognitive load, then the ease of operation is improved, but the productivity decreases due to time consumption

Engineering Contradiction:

Improveease of NOTAM message sortingVSAvoidpilot productivity

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent implements self-service by enabling the system to automatically sort, prioritize, and present NOTAM messages without requiring manual intervention from the pilot. The machine learning algorithms autonomously analyze message content, identify critical information, and organize it in a user-friendly format, allowing the system to serve itself in the information processing task while making the output easily operable for the pilot.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250384775A1Electronic system and method for assisting a civil aircraft operator in decision making with the elaboration of aeronautical indicator(s), related civil aircraft and computer program

Publication Date: 2025.12.18 THALES SA

AI summary

An electronic decision-making assistance system for an operator of a civil aircraft, including an electronic display device for displaying information, an electronic production device for producing aeronautical indicators, including an acquisition module for acquiring at least one aeronautical information message including a header and a useful part, the useful part including several data fields, including a free-format text field called free field, a calculation module for calculating a plurality of aeronautical indicators for each aeronautical information message by applying an artificial intelligence (AI) algorithm to the message, the AI algorithm receiving the free field as input and delivering the indicators as output, the indicators being distinct from the data contained in the message, and a display module for displaying a readout of the aeronautical indicators.