Label Generation

[vbramhadevi]

Description

Create a rule-based labeling system to assign flight phase/event labels to the collected dataset. The labeled dataset will be used later for machine learning. All outputs (code + labeled dataset) must be stored inside the inference/ folder.

Tasks

• Create a labeling script (e.g., label_generator.py) inside inference/
• Read input data from inference/raw_flight_data.csv
• Define rule-based conditions using parameters like altitude, velocity, vertical_speed, heading, roll, and g_force
• Implement labeling for the following events: TAXI, TAKEOFF, CRUISE, APPROACH, LANDING, TURN_LEFT, TURN_RIGHT, HIGH_SPEED, LOW_SPEED, HIGH_ALTITUDE, LOW_ALTITUDE, HIGH_G_FORCE, NORMAL_FLIGHT
• Apply rules row-by-row to generate labels
• Add a new column event_label
• Save output as inference/labeled_flight_data.csv
• Validate labels manually on sample rows
• Ensure no missing labels
• Push code and labeled dataset to inference/

Acceptance Criteria

• inference/labeled_flight_data.csv is created with event_label column
• All specified events are implemented and used correctly
• Every row has a valid label (no missing values)
• Code is clean, readable, and documented