The Intelligent Railway Management System leverages machine learning algorithms, IoT sensors, and geolocation services to optimize train schedules, predict delays, and enhance passenger experience. By integrating the Random Forest and Panda Forest algorithms, the system accurately forecasts train delays based on weather, passenger load, and operational factors. A dedicated Android app and web platform ensure seamless communication between users, station masters, and administrators.

Key Features

Real-time train delay prediction using AI models
Optimized scheduling to reduce wait times and congestion
Passenger load forecasting for better resource allocation
Weather impact analysis to improve operational efficiency
Live train location tracking via GPS
Google Maps integration for precise distance and route tracking

Challenge

Managing multiple variables, such as weather conditions, passenger load, and operational delays, to provide accurate predictions.

Solution

Implemented advanced machine learning models (Random Forest) and IoT-based data collection to enhance prediction accuracy. Integrated Google Maps API for real-time train tracking and optimized route planning.

Railway System

Key Features

Challenge

Solution