Real-time-tracking

Project Overview

This project is a comprehensive real-time bus tracking application that leverages modern web technologies and big data processing to provide live bus location tracking and analytics.

Technologies Used

1. Frontend: Leaflet.js for interactive mapping
2. Backend: Python, Flask
3. Big Data Processing: Apache Hadoop / HDFS

Installation

1. Clone the repository

   git clone https://github.com/IMvision12/Real-time-tracking
   cd Real-time-tracking

2. Set up Python virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

3. Navigate to your Hadoop installation directory

4. Locate and edit the configuration files:

   • etc/hadoop/core-site.xml
   • etc/hadoop/hdfs-site.xml
   • Ensure network and storage paths are correctly specified

5. Start Hadoop Services

   • Open a terminal with administrator privileges
   • Run the Hadoop cluster startup command: start-all.cmd
   • Verify Hadoop services are running:
     • Check NameNode and DataNode status
     • Confirm no startup errors in the console

6. Start Data Collection Service

   • Update the API key in config.py and leaf.js files
   • Open a new terminal
   • Navigate to the project's src directory: cd Real-time-tracking/src
   • Launch the MTA Bus API data fetching script: python main.py
   • Verify data ingestion is working correctly
     • Check console logs for successful API connections
     • Monitor initial data retrieval process

7. Launch Flask Web Application

   • pen another terminal
   • Ensure you're in the Real-time-tracking project directory
   • Start the Flask web application: python app.py