Project Overview:

The Big Data-Based Traffic Congestion Predictor is a smart web-based system that uses large-scale traffic data (live or historical) to analyze and predict traffic congestion in various city zones. It integrates Big Data technologies, machine learning, and real-time web visualization to help users and traffic management authorities make better route and traffic flow decisions.

This project simulates a smart city solution, applicable in public transport planning, route optimization, and intelligent traffic control.

Key Features:

1.  Real-time traffic data ingestion (or simulation)

2.  Heatmap of congestion-prone areas

3.  ML-based prediction of traffic jams (zone-wise)

4.  Time-series analysis (hour/day/week/month)

5.  Alternate route suggestions (optional)

6.  Admin dashboard to monitor city traffic trends

7.  Trend charts for specific zones/roads

Technology Stack:

Backend (Choose One):

• Node.js + MongoDB (for high-speed document storage)

• Java + Hadoop/HDFS + Spark (for distributed data processing)

• PHP + MySQL (simplified for simulation)

Frontend:

• HTML, CSS, Bootstrap

• JavaScript (Google Maps API, Chart.js, Leaflet.js for heatmaps)

• AJAX for live updates

Big Data + ML:

• Apache Kafka or data simulator for real-time traffic feed

• Apache Spark or Pandas/NumPy (Python) for processing

• ML Models:

  • Random Forest / XGBoost for congestion prediction

  • Time Series (ARIMA/LSTM) for temporal forecasting

How It Works:

1. Data Collection:

   • Ingest real-time traffic feeds (simulated or via APIs like Google Maps, HERE, TomTom)

   • Data points: speed, vehicle count, location, timestamp

2. Data Processing (Big Data Tools):

   • Store and clean traffic records using Spark or Hadoop

   • Extract features: average speed, density, day/time, weather (optional)

3. Machine Learning Model:

   • Train ML model to predict traffic congestion level (Low, Medium, High) based on time, location, and vehicle density

   • Predict congestion for the next hour/day

4. Web Dashboard:

   • Display congestion heatmaps on city map

   • Show congestion forecasts

   • Display historic trends, average delay per area, and alerts