Live-Traffic-Management-System🚦

AI-powered real-time traffic prediction, congestion detection & dashboard visualization.
This project provides a complete real-time traffic management system that predicts congestion using machine learning, visualizes live traffic flow, and assists city/roadway authorities in decision-making. It integrates feature engineering, a trained Isolation Forest model, and a modern dashboard for visualization.

Key Features

1. Machine Learning–based Congestion Prediction

Uses Isolation Forest to detect anomalies in traffic patterns
Predicts high, medium, and low congestion zones
Scaler applied consistently across pipeline

2. Data Preprocessing & Feature Engineering

Extracts volume, density, speed, weather influence, and time-based features
Outlier cleaning & normalization
Automatic feature scaling and saving for inference

3. Interactive Dashboard

Live map heat visualization
Congestion severity indicators
Trend charts and zone-based predictions
Filter by time, road ID, city area

4. Real-time Update Ready

Architecture prepared for REST API integration
Supports streaming data from sensors, CCTV, IoT devices

Tech Stack

Streamlit

How to Run the Project

1️⃣ Run Preprocessing / EDA Script on colab Traffic.py
2️⃣ Launch Dashboard
Streamlit: streamlit run dashboard/app.py