Voice Recognition Aircraft Identification System
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Solution Overview
Problem
The increasing workload of air traffic controllers due to visual searches on radar screens and potential errors in selecting information about aircraft, exacerbated by the 'funnel' phenomenon during approach and random flight patterns, necessitates a more efficient system for identifying and controlling aircraft in monitored air sectors.
Innovation Solution
A system utilizing voice recognition to analyze oral communications between air traffic controllers and pilots, coupled with management means to compare and validate data, dynamically highlighting relevant aircraft on displays and reducing recognition errors through coupling with stored identifiers and flight parameters, allowing for real-time communication tracking and error reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If air traffic controllers perform visual searches on radar screens to identify aircraft, then aircraft identification can be achieved, but controller workload increases significantly
Solution Approach 1:
The patent replaces the mechanical visual search process with an automated voice recognition and data processing system. The system captures oral communications, identifies speaker identities through voice recognition, and automatically displays relevant aircraft information on the radar screen, eliminating the need for manual visual searching by controllers.
Solution Approach 2:
The system enables self-service by automatically performing aircraft identification and information retrieval without requiring controller intervention. The automated system processes voice communications, matches them with aircraft data, and presents the information proactively to the controller, making the identification process autonomous.
2Loss of information
If air traffic controllers manually select and enter aircraft information, then data can be recorded, but errors in information selection and entry increase
Solution Approach 1:
The system implements feedback by automatically verifying voice-recognized data against stored aircraft information and comparing it with data entered by the controller. This cross-verification mechanism detects and prevents errors in information selection and entry, ensuring data accuracy through automated feedback loops.
Solution Approach 2:
The patent introduces asymmetry in the data entry process by automatically generating aircraft information from voice recognition and presenting it to the controller for confirmation, rather than requiring the controller to manually enter all data. This asymmetric approach reduces manual input errors while maintaining data accuracy through automated generation and verification.
3Productivity
If voice recognition is used to analyze oral communications, then controller workload is reduced, but recognition errors due to transmission noise increase
Solution Approach 1:
The system performs preliminary action by pre-processing the voice signal through filtering before recognition. The transmission noise is filtered out in advance, and the cleaned signal is then subjected to voice recognition, significantly improving recognition accuracy while maintaining high processing efficiency.
Solution Approach 2:
The patent introduces an intermediary filtering stage between the voice communication and the recognition process. This intermediary component removes transmission noise and artifacts from the audio signal, providing a cleaner input to the voice recognition system and thereby improving recognition reliability without reducing processing efficiency.
4Loss of information
If real-time display of communicating aircraft is implemented, then situational awareness is improved, but system complexity increases
Solution Approach 1:
The patent merges the voice recognition system with the existing radar display system. The automated aircraft identification and communication tracking functions are integrated into the conventional radar interface, allowing real-time display of communicating aircraft without requiring a separate complex display system. This merging leverages existing infrastructure to reduce overall system complexity.
Data Source
Figure 1~2
AI summary
The system has voice recognition units (RV) analyzing oral communications exchanged between an aerial controller and pilots of an aircraft provided in an aerial sector (SA) to be monitored. Management units (GES) compare data delivered by the voice recognition units and stored identifiers (LID) that are representatives of respective aircrafts provided in the aerial sector. Display units (EA) display a space including the aerial sector and the aircraft provided in the space. Visualization units are equipped on the display units. An independent claim is also included for a method for assistance to identify and control an aircraft in an aerial sector to be monitored.