Comprehensive capabilities built into the A.U.R.A. system
A.U.R.A. continuously ingests sensor data from 28+ environmental sensors distributed across the spacecraft. Data is processed and displayed in real-time with automatic refresh every second, ensuring mission operators always have current system status information at their fingertips.
Advanced ML algorithms automatically detect anomalies and predict maintenance requirements before failures occur. The system uses Isolation Forest for unsupervised anomaly detection and can be extended with supervised learning models.
An interactive digital representation of the spacecraft enables operators to visualize system states, test maintenance procedures, and validate repairs before implementation. The digital twin uses reinforcement learning models trained on realistic operational scenarios.
Comprehensive role-based access control ensures appropriate data visibility and system permissions. The system supports three user roles with different capabilities and data access levels.
A.U.R.A. monitors all critical life support subsystems required for crew safety and mission success. Each subsystem is continuously evaluated for normal operation and maintenance requirements.
The system provides comprehensive tools for analyzing historical sensor data, identifying trends, and generating actionable reports for mission planning and maintenance scheduling.
A.U.R.A. is optimized for real-time operations in the resource-constrained environment of spacecraft systems, with proven performance improvements over traditional reactive maintenance approaches.
A.U.R.A. leverages modern, proven technologies for reliability, maintainability, and extensibility in spacecraft operations.