ENHANCING FLIGHT SAFETY TRAINING WITH AI-GENERATED TELEMETRY DATA FOR MISSION READINESS

Obtaining simulated or pre-recorded telemetry data is often restricted due to classification or proprietary constraints, limiting its use for training, pre-mission workups and flight safety preparation. In many cases operators only encounter real telemetry data at the first live test event. The use of AI driven tools allows for the generation of realistic flight safety values, enabling the production of simulated telemetry data streams. These values can be manipulated to represent a range of realistic flight conditions, providing the necessary complexity and situation evolution seen in high dynamic failure modes. These data can therefore be used to enhance training scenarios, by ensuring that flight safety personnel are prepared for a range of complex and realistic failure conditions. In addition, other AI-based tools have enabled historical paper records (eg Apollo 11 and past missions) to be digitised in simulated telemetry IRIG 106 Chapter 4 Pulse Code Modulation (PCM) streams and then utilised for system checkout and technician training.

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Publication Details

Journal
UA Campus Repository (The University of Arizona)
Published
2025-10-01
Primary Topic
Human-Automation Interaction and Safety
Type
article
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article

ENHANCING FLIGHT SAFETY TRAINING WITH AI-GENERATED TELEMETRY DATA FOR MISSION READINESS

Benjamin Hennessy
UA Campus Repository (The University of Arizona)
Human-Automation Interaction and Safety
article

ENHANCING FLIGHT SAFETY TRAINING WITH AI-GENERATED TELEMETRY DATA FOR MISSION READINESS

Benjamin Hennessy
article en

Abstract

Obtaining simulated or pre-recorded telemetry data is often restricted due to classification or proprietary constraints, limiting its use for training, pre-mission workups and flight safety preparation. In many cases operators only encounter real telemetry data at the first live test event. The use of AI driven tools allows for the generation of realistic flight safety values, enabling the production of simulated telemetry data streams. These values can be manipulated to represent a range of realistic flight conditions, providing the necessary complexity and situation evolution seen in high dynamic failure modes. These data can therefore be used to enhance training scenarios, by ensuring that flight safety personnel are prepared for a range of complex and realistic failure conditions. In addition, other AI-based tools have enabled historical paper records (eg Apollo 11 and past missions) to be digitised in simulated telemetry IRIG 106 Chapter 4 Pulse Code Modulation (PCM) streams and then utilised for system checkout and technician training.

UA Campus Repository (The University of Arizona)
Openalex Percentile: Top 20%
Human-Automation Interaction and Safety
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