AI-Driven Aircraft Crew Operational State Monitoring and Training System
Legal Citation
Summary of the Inventive Concept
A next-generation aircraft crew operational state monitoring system that leverages artificial intelligence, machine learning, and blockchain technology to predict and prevent pilot errors, enhance operational safety, and provide immersive training simulations.
Background and Problem Solved
The original patent disclosed a system for monitoring the operational state of an aircraft crew, but it had limitations in terms of accuracy, reliability, and adaptability. The new inventive concept addresses these limitations by integrating AI, ML, and blockchain technologies to provide a more robust, secure, and efficient system for monitoring and training aircraft crews.
Detailed Description of the Inventive Concept
The AI-driven aircraft crew operational state monitoring and training system comprises a neural network-based pilot state determiner, a blockchain-based data storage unit, and a decentralized pilot state determiner. The system receives first crew monitoring data having a high design assurance level and second crew monitoring data having a lower design assurance level. The AI algorithms process the data to determine at least one pilot state, predict potential pilot errors, and provide personalized recommendations to mitigate safety risks. The system also integrates with a virtual or augmented reality platform to provide immersive training simulations, and includes a biometric sensor unit to monitor the crew's physiological and psychological responses during the simulations.
Novelty and Inventive Step
The new inventive concept introduces the use of AI, ML, and blockchain technologies to aircraft crew operational state monitoring, which is a significant departure from the original patent's deterministic algorithms and finite-state machines. The integration of these technologies enables the system to predict and prevent pilot errors, enhance operational safety, and provide immersive training simulations, making it a novel and non-obvious advancement in the field.
Alternative Embodiments and Variations
Alternative embodiments of the inventive concept could include the use of different AI algorithms, such as deep learning or reinforcement learning, or the integration of additional data sources, such as weather or air traffic control data. The system could also be adapted for use in other industries, such as maritime or rail transportation, or for monitoring and training other types of operators, such as surgeons or astronauts.
Potential Commercial Applications and Market
The AI-driven aircraft crew operational state monitoring and training system has significant commercial potential in the aviation industry, particularly for airlines, aircraft manufacturers, and aviation authorities. The system could also be marketed to other industries, such as maritime or rail transportation, or to organizations that require operator training and monitoring, such as hospitals or space agencies.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Aviation safety systems, human factors engineering, and operational monitoring technologies with expertise in aircraft crew performance assessment, sensor integration, and state determination algorithms
Person of Ordinary Skill (PHOSITA) Profile
A professional with advanced engineering degrees in aerospace, electrical, or computer engineering, specialized knowledge of aviation safety systems, experience with state machine design, sensor data processing, and human performance monitoring technologies
Obviousness Rationale
A PHOSITA would recognize that applying contemporary AI and machine learning techniques to the source patent's deterministic crew monitoring framework represents a predictable technological evolution. The fundamental architecture of receiving multi-level monitoring data and determining pilot states remains consistent, with AI serving as an enhanced algorithmic approach to state determination. The integration of blockchain, neural networks, and immersive training technologies are logical extensions of existing crew monitoring principles.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,324 |
|---|---|
| Title | System for monitoring the operational status of an aircraft crew, and associated method |
| Assignee(s) | DASSAULT AVIATION |