AI Smart Ambulance Detection & Priority Traffic Preemption System
Intelligent urban traffic control system detecting emergency ambulances via acoustic siren analysis and YOLO computer vision to automate green light clearance.
### AI Smart Ambulance Detection & Traffic Preemption Engine (FYP Complete)
Emergency ambulances worldwide lose critical survival minutes trapped in urban traffic congestion. This multi-modal AI engineering project combines audio spectral analysis (MFCC + CNN siren classifier) with real-time video detection (YOLOv8 Emergency Vehicle classifier) to trigger dynamic traffic signal phase preemption, granting ambulances uninterrupted green corridors.
#### 🧠 Architecture & Tech Stack:
- **Audio Classifier**: Mel-Frequency Cepstral Coefficients (MFCC) with 1D CNN recognizing emergency sirens with >95% accuracy in noisy traffic
- **Visual Detector**: YOLOv8 nano fine-tuned on ambulance & emergency vehicle datasets (>30 FPS)
- **Traffic Controller Algorithm**: Dynamic queue clearing logic interfacing with hardware traffic lights via GPIO / Serial
- **Web Telemetry**: Real-time Django command dashboard with emergency vehicle GPS map tracking and clearance logs
What's Included in the Package:
- Complete Python & YOLOv8 Source Code
- Pre-trained Siren Audio & Vehicle Detection Models
- Traffic Signal Controller Hardware Logic Code
- Complete 55+ Page IEEE Project Report (DOC & PDF)
- Defense Presentation Slides (PPTX)
- Installation & Run Video Guide
Key Features
Specifications
Community Questions & Answers
Have a question about compatibility, code, or delivery? Ask our engineering team or see what other Pakistani makers asked.
Sir laptop pe bina GPU k run ho jaye ga for final viva demonstration?
Yes! The YOLOv8 inference is optimized with OpenCV DNN backend to run smoothly on standard Intel Core i5/i7 CPU with 8GB RAM at 25-30 FPS without needing a dedicated gaming GPU.
Assalam o Alaikum, bhai is project ka source code Python 3.10/3.11 pe test kia hua hai? Aur kya IEEE report editable MS Word doc format me mile gi?
Walaikum Assalam Hamza! Yes, 100% verified on Python 3.10 and 3.11. The package includes full Django web app source code, pre-trained YOLO acoustic/vision weights, and a 55+ page IEEE formatted report in both editable MS Word (.docx) and PDF formats, plus PPT defense slides.