This directory contains the rule-based labeling system for flight telemetry data, used to prepare datasets for machine learning training.

The labeling system assigns flight phase and event labels to raw telemetry data based on rule-based thresholds for parameters like altitude, velocity, vertical speed, heading, roll, and g-force.

• label_generator.py - Main labeling script with rule-based logic
• validate_labels.py - Validation script for labeled data quality checks
• generate_sample_data.py - (Optional) Sample flight data generator for testing
• requirements.txt - Python package dependencies
• Data/raw_flight_data.csv - Input: Raw telemetry data (not tracked in git)
• Data/labeled_flight_data.csv - Output: Labeled dataset ready for ML training

The system labels data with the following 13 event types:

• TAXI - Ground operations (altitude < 50ft, speed < 30 knots)
• TAKEOFF - Transition from ground to air (low altitude, climbing, 50-100 knots)
• CRUISE - Steady flight at altitude (altitude > 3000ft, stable vertical speed)
• APPROACH - Descending for landing (500-3000ft, descending)
• LANDING - Final approach and touchdown (altitude < 500ft, descending)

• TURN_LEFT - Left turn (roll < -5° or heading change < -3°/s)
• TURN_RIGHT - Right turn (roll > 5° or heading change > 3°/s)

• HIGH_SPEED - Velocity > 200 knots
• LOW_SPEED - Velocity < 60 knots (while airborne)

• HIGH_ALTITUDE - Altitude > 10,000 feet
• LOW_ALTITUDE - Altitude < 1,000 feet (while airborne)

• HIGH_G_FORCE - G-force > 1.5g
• NORMAL_FLIGHT - Default steady flight (none of the above conditions)

Python 3.7 or higher required

Install dependencies: Using pip py -m pip install -r requirements.txt Or install packages directly py -m pip install pandas numpy

1. Collect flight data (using data_logger.py) cd Data py data_logger.py
2. Generate labels cd .. py label_generator.py
3. Validate labels py validate_labels.py
4. Use labeled data for ML training