AI-Powered Traffic Management: AmbuRouteAI

Revolutionizing Emergency Vehicle Traffic Flow with AI 🚑

In the face of increasing urban congestion, ensuring that emergency vehicles like ambulances reach their destinations without delay is critical. AmbuRouteAI is an innovative AI-driven traffic management system that leverages cutting-edge object detection and real-time traffic light control to create a seamless pathway for ambulances. By harnessing the power of YOLOv8 for detection and OpenCV for traffic simulation, AmbuRouteAI significantly reduces ambulance response times and enhances emergency healthcare logistics.

🔧 Key Features

✅ Real-time Ambulance Detection – Utilizes YOLOv8 AI to detect ambulances from live traffic feeds.

✅ Intelligent Traffic Signal Control – Dynamically adjusts traffic lights using OpenCV when an ambulance is detected.

✅ Live Video Processing – Supports webcams or CCTV camera feeds to analyze real-time road conditions.

✅ Seamless Integration – Can be extended into IoT-enabled smart city infrastructure.

✅ Scalability – Designed for integration with Google Maps API for real-time route optimization.

🛠️ Tech Stack

Component

Technology/Tool

AI Model

YOLOv8 (Ultralytics)

Computer Vision

OpenCV, NumPy

Backend

Python

Traffic Simulation

OpenCV

Live Video Input

Webcam / CCTV Feed

📜 How It Works

1️⃣ AI-Powered Detection

AmbuRouteAI employs the YOLOv8 model to analyze live traffic feeds and identify ambulances in real time.

2️⃣ Smart Traffic Light Control

When an ambulance is detected, the system dynamically changes the traffic light to green, ensuring a clear path for emergency vehicles.

3️⃣ Visual Alerts & UI

The system overlays bounding boxes on detected ambulances and provides a simulated traffic signal interface.

4️⃣ Future-Ready Extensibility

AmbuRouteAI can integrate with Google Maps API and IoT sensors, enabling comprehensive smart city traffic management.

📥 Installation & Setup

To run AmbuRouteAI locally, follow these steps:

1. Clone the Repository

git clone https://github.com/mantreshkhurana/AmbuRouteAI.git

cd AmbuRouteAI

1. Set Up a Virtual Environment

python -m venv venv

source venv/bin/activate  # On Windows, use 'venv\Scripts\activate'

1. Install Dependencies

pip install -r requirements.txt

1. Download YOLOv8 Model

Download yolov8n.pt from Ultralytics and place it in the project directory.

1. Run the Application

python main.py

🎯 Future Enhancements

Google Maps API Integration – Optimize routes using live traffic data.

IoT-Based Smart Traffic Signals – Deploy with Raspberry Pi & Arduino for real-world applications.

Hospital Alert System – Notify hospitals about incoming emergency patients.

Mobile App Interface – Develop an app for real-time ambulance tracking and traffic updates.

👨‍💻 Author

Mantresh Khurana

For more details and access to the source code, visit the AmbuRouteAI GitHub Repository: https://github.com/mantreshkhurana/AmbuRouteAI