Developed an AI-powered visual inspection solution to detect residue on phosphate wagons, using real-time video analysis. The system includes an application for inspection configuration, result analysis, and KPI monitoring.
During my Data Scientist internship at ONCF Group, I worked on digitalizing and automating an industrial visual inspection process.
The project focused on detecting residue accumulation on railway wagons through computer vision and real-time video analysis.
I developed an AI-based inspection pipeline and integrated it into an application supporting system configuration, inspection monitoring, results analysis, and KPI tracking.
The work aimed to improve inspection reliability and support operational decision-making.
Shared fields: Computer Vision, Industrial AI
Developed an AI-powered solution combining computer vision and OCR to identify railway components and simplify spare-parts searches. The project included data preparation and tools for continuously enriching the component reference dataset.
Shared fields: Computer Vision
Designed and deployed a low-cost embedded driving assistance system that recognizes Moroccan traffic signs in real time and provides multilingual voice guidance to help drivers stay informed while reducing visual distraction.