This project helped me understand how to implement the following features:
Multi-Model Classification: LightGBM, XGBoost, and Random Forest models for failure type prediction
Hybrid Time Series Forecasting: LSTM-based engine temperature prediction with intelligent trend analysis for extreme temperatures Multiple Issue Detection: Simultaneous detection of engine, brake, and tire issues
Intelligent Anomaly Handling: Smart anomaly indication that only triggers maintenance when other values are normal
Safety-Critical Temperature Analysis: Emergency detection for dangerous engine temperatures above 120°C