🚦 Street Sense – Real-Time Traffic Monitoring System

Street Sense is a real-time traffic analysis system designed to detect and track vehicles and estimate their speeds using only a single webcam. This project aims to provide a cost-effective, intelligent solution for monitoring traffic flow and identifying speed violations.

⚠️ This project is under active development — new features and improvements are being added continuously.

📌 Features

• 🚗 Vehicle Detection using the YOLO object detection algorithm
• 🎯 Speed Estimation based on real-time tracking data
• 📹 Works with any webcam or video input
• 🧠 Single-camera solution — no radar, lidar, or multiple sensors required
• 📊 Logs vehicle data including:
  • Detected speed
  • Timestamp
  • Snapshot filename
• 📁 Saves detection results to a CSV file

🧪 Technologies Used

• YOLO (You Only Look Once) – Object detection
• OpenCV – Video processing and object tracking
• Python – Core implementation
• CSV – Data logging

🎬 Demo Video Source

Video used for development/testing:

demo_01.mp4

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demo_02.mp4

🛠️ Setup Instructions

1. Clone the repository:

   git clone https://github.com/yourusername/street-sense.git
   cd street-sense```
   

2. Install required dependencies:

   pip install -r requirements.txt

3. Run the main script:

   python main.py

📂 Output

• snapshots/: Contains images of detected vehicles.
• log.csv: CSV file containing timestamp, speed, and snapshot filename for each detection.

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🚧 Under Development

I'm working on:

• Enhancing object tracking for better accuracy
• Calibrated speed estimation using camera parameters
• UI dashboard for visualizing real-time stats

Stay tuned for updates! 😊