AI
Computer Vision
YOLO
OpenCV
Road Safety
Python
AI-Powered Road Traffic Analysis System
An intelligent solution to transform traffic scenes into actionable dashboards, aiming to reduce accidents and corruption.
About the Project
Facing the alarming increase in road accidents in Cameroon, this project uses AI to provide precise data to authorities. The goal is to move from 'gut-feeling' management to informed decision-making backed by precise measurement instruments at intersections and critical road sections.
Features & Impact
- Real-time detection and classification (cars, motorcycles, buses, trucks) via YOLO.
- Multi-object tracking to reconstruct trajectories and uniquely identify each vehicle.
- Precise speed measurement (km/h) through scene calibration and NumPy calculations.
- Automatic violation detection (speeding beyond 60 km/h).
- Structured report generation (CSV) to assist municipal or governmental decision-making.
- Potential for digital fine payment to eradicate road-side corruption.
Technical Architecture
Designed to run on standard hardware (Core i5), the system combines YOLO for fast detection, OpenCV for video stream processing, and NumPy for physical calculations. This approach demonstrates that local technological sovereignty is possible using open tools to address national road safety challenges.
Published by Sat Magazine