Скачать или смотреть 🚗 Real-Time Vehicle Speed Detection & Monitoring System Using Computer Vision & Deep Learning

I’m excited to showcase a fully functional, real-time Vehicle Speed Monitoring System designed to accurately detect, track, and measure vehicle speed using AI and computer vision.

This system leverages YOLO-based vehicle detection, world-coordinate mapping, and robust multi-object tracking to deliver stable, lane-aware, production-ready speed analytics from a single camera.


🔥 Where This System Is Useful

Ideal for:

✔ Speed enforcement & violation detection
✔ Smart traffic surveillance systems
✔ Highway & expressway monitoring
✔ Accident-prone zone speed analysis
✔ Toll plaza & flyover monitoring
✔ Industrial vehicle speed regulation
✔ Parking & campus speed control
✔ Smart city traffic analytics

✨ Key Features
🔹 1. Real-Time Vehicle Speed Estimation

✔ Accurate speed calculation in km/h
✔ Per-vehicle speed tracking using unique IDs
✔ Live speed overlay on bounding boxes
✔ Maximum speed captured per vehicle
✔ Stable results using temporal smoothing


🔹 2. AI-Powered Vehicle Detection (YOLO)

High-accuracy vehicle detection supporting:

✔ Cars
✔ Buses
✔ Trucks
✔ Two-wheelers (optional)

Reliable performance in:

✔ Dense traffic
✔ Low-light conditions
✔ Rainy & complex road scenes


🔹 3. World-Coordinate Speed Calibration

✔ Pixel-to-meter conversion using:

Homography-based calibration (4-point mapping)

Fallback meter-per-pixel scaling

✔ Real-world speed estimation instead of raw pixel motion
✔ Easily adaptable to different camera angles


🔹 4. Intelligent Vehicle Tracking & Motion Analysis

✔ Stable tracking IDs across frames
✔ Frame-wise motion history per vehicle
✔ Linear regression-based velocity estimation
✔ Noise-free speed using smoothing filters

Ensures:

✔ No speed spikes
✔ No duplicate vehicles
✔ Accurate maximum speed measurement


🔹 5. Region-Based Speed Monitoring (Polygon ROI)

✔ Define custom road regions using polygons
✔ Speed is calculated only when vehicle is inside the ROI
✔ Eliminates false measurements from adjacent lanes or sidewalks


🔹 6. Interactive Tkinter GUI Dashboard

User-friendly desktop interface with:

✔ Video file / live camera support
✔ Polygon region selection tool
✔ Real-time speed visualization
✔ Vehicle ID & bounding box display
✔ Auto-snapshot capture at peak speed
✔ Speed history table with previews
✔ CSV export for reports


🔹 7. Vehicle Logging, Snapshots & Reporting

For every tracked vehicle, the system records:

✔ Vehicle ID
✔ Vehicle type
✔ Timestamp
✔ Maximum speed (km/h)
✔ Auto-captured snapshot
✔ CSV export for analytics & audits

🚀 Why This System Matters

This project demonstrates how AI + computer vision can replace traditional hardware-based speed guns using pure video analytics, making it:

✔ Cost-effective
✔ Scalable
✔ Camera-only
✔ Smart-city ready


💰 Pricing

I am offering the complete Vehicle Traffic Lane Analysis Project at:

🎉 ₹699 — Full Project + Complete Documentation

📦 Includes:

✔ Full Python source code
✔ Tkinter-based GUI dashboard
✔ YOLOv11 vehicle detection
✔ Vehicle tracking with stable IDs
✔ Real-time vehicle speed estimation (km/h)
✔ World-coordinate speed calibration (pixel → meter)
✔ Region / polygon-based speed monitoring
✔ Maximum speed capture per vehicle
✔ Automatic vehicle snapshot saving
✔ Speed history logging
✔ CSV report generation
✔ Step-by-step setup & calibration guide
✔ Full project walkthrough
✔ Installation & configuration support

🚀 Want to implement a custom AI project?
I also work on end-to-end solutions in:
🤖 Machine Learning | 🧠 Deep Learning | 👁️ Computer Vision | 🎨 Generative AI | 💬 NLP | 🧩 RAG / Agentic RAG | ⚙️ NVIDIA Jetson | 🍓 Raspberry Pi |🐳 Docker | ☁️ Cloud Services (AWS | Google Cloud | Microsoft Azure)

Let’s connect and bring your AI ideas to life!


📧 Email: [email protected]
📸 Instagram:  / pandian449  
🔗 LinkedIn:  / pandian-p-3b0553230  

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