Bharat in Betastartup field guide
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No. 1287Problem statementDefence and aerospace

AI-Enabled Real-Time Digital Twin System for Health Monitoring, Fault Prediction and Mission Reliability Enhancement of Aero Piston Engines used in MALE UAVs.

Source

Source summary

The source proposes a digital twin for aero-piston engine health monitoring in MALE UAVs, combining telemetry, physical models, operational history and AI analytics. Its high-level scope covers anomaly detection, degradation and remaining-life estimates, replay/simulation and maintenance dashboards, demonstrated using simulated or real engine data. The atlas does not reproduce detailed military mission optimization or propulsion implementation requirements, and reliability gains remain proposed outcomes.

No. 173Problem statementDefence and aerospace

AI-ML Modelling - AI-ML models for space applications

Develop AI/ML models for large space datasets. The source discusses Earth-observation and spacecraft telemetry analysis, as well as support for large satellite constellations, including relative positioning, communications and end-of-life management.

No. 360Problem statementDefence and aerospace

Data analytics for air trajectory

Develop a machine-learning algorithm using historical aircraft trajectories to identify anomalous movements and departures from authorised routes. The source provides that mechanism and data basis but no further operational or performance specification.

No. 366Problem statementDefence and aerospace

Predictive preventive and prescriptive machine monitoring

Develop a modular platform monitoring ship machinery in real time through parameters such as temperature, pressure and sound. AI should support predictive and preventive maintenance, while the system also gives ship staff proposed corrective actions when faults arise. The prescriptive component is part of the original request, not later commentary.