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Egypt Metro AI Models

Overview

The Egypt Metro AI Models repository contains machine learning models used for crowd prediction, route optimization, and chatbot support. These models are powered by TensorFlow, Keras, and Natural Language Processing (NLP) techniques. The AI component helps to provide real-time insights into crowd density and suggests optimized routes for users based on historical data and AI predictions.

Features

  • Crowd Prediction: Predicts train congestion based on time of day and historical data.
  • Route Optimization: Suggests the most efficient travel routes based on user preferences and live data.
  • Chatbot: NLP-based chatbot to assist users with FAQs and navigation.
  • Anomaly Detection: Detects unusual patterns in fault reporting data and flags them for further analysis.

Installation

Prerequisites

  • Python 3.9+
  • TensorFlow 2.x
  • Scikit-learn
  • Pandas
  • NumPy

Setup

  1. Clone the repository: 
    git clone https://github.com/egypt-metro/egypt-metro-ai.git
  2. Navigate to the project directory:

cd egypt-metro-ai Create and activate a virtual environment:

bash Copy code python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate Install dependencies:

bash Copy code pip install -r requirements.txt Running the Models Crowd Prediction Model: To train the crowd prediction model, run:

bash Copy code python train_crowd_model.py Route Optimization Model: To train the route optimization model, run:

bash Copy code python train_route_model.py Chatbot: To train and run the chatbot model, use:

bash Copy code python train_chatbot.py python run_chatbot.py Example Usage Crowd Prediction: To make a prediction on crowd density:

bash Copy code python predict_crowd.py --time "08:00" --train_line "Line 1" Route Optimization: To suggest optimized routes:

bash Copy code python predict_route.py --start_station "Station A" --end_station "Station B"