Flight Telemetry Anomaly Detection

This project implements a machine learning system to detect anomalies in aircraft telemetry sensor data.

The system simulates telemetry streams such as temperature, pressure, vibration, fuel flow, and engine RPM.

Isolation Forest is used to detect abnormal sensor patterns that may indicate potential system faults.

Pipeline Telemetry Data → Feature Scaling → Isolation Forest → Anomaly Detection

Technologies Python Pandas Scikit-Learn Matplotlib

Applications Aircraft engine monitoring Predictive maintenance Aerospace telemetry analysis