🚦 Smart Traffic Control System

Traffic monitoring, vehicle & pedestrian detection, and intelligent signal management

📌 Project Goals

• Detect & Count Vehicles from live traffic camera streams using computer vision.
• Optimize Traffic Light Timings based on real-time data for efficient flow.
• Enhance Safety for pedestrians and vehicles, minimizing crash risks.

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⚙️ Installation & Setup

Requirements

• Arduino IDE installed and running.
• Serial Monitor in Arduino IDE should be open.
• OpenCV installed with all necessary dependencies.
• Configured and connected cameras for live traffic monitoring.

Steps

1. Install Arduino IDE and ensure your microcontroller is connected.
2. Open the Serial Monitor in Arduino IDE.
3. Install OpenCV (pip install opencv-python) and configure your cameras.
4. Run the traffic detection script.

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Prototype & Implementation

Example Frames:

Clear View	Vehicle Detection (1)	Vehicle Detection (2)

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📄 Documentation

Markdown Versions

• Project Info (English)
• Project Info (Russian)
• Project Info (Turkmen)

DOCX Versions

• Smart Traffic (English)
• Smart Traffic (Russian)
• Smart Traffic (Turkmen)

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Features at a Glance

• Real-time vehicle counting & classification
• Dynamic traffic light control for smoother flow
• Pedestrian detection to enhance crossing safety
• Flexible camera input configuration
• Works with Arduino-based hardware integration