Subject #8 AI-Powered Smart Parking Detection PFE

Project overview

• A complete smart-parking solution combining real-time computer vision and a user-friendly mobile application.
• Street cameras analyze live video streams to detect vehicles and identify available parking slots using AI, with detected free spots displayed instantly in a Flutter mobile app.
• Objectives: reduce parking search time, optimize city traffic flow and provide an efficient, modern parking experience.

Main responsibilities

• Develop and train object detection/segmentation models to detect parked vehicles and infer free parking slots using frameworks such as TensorFlow or PyTorch.
• Build and integrate a real-time computer vision pipeline (capture → detection → tracking → slot availability inference) using Python and OpenCV.
• Design and implement REST APIs and backend services to serve detection results and persist data in PostgreSQL.
• Integrate AI outputs with the Flutter mobile application so users can view live parking availability and receive updates before arriving.

Required profile & skills

• Basic knowledge of Python and AI (object detection, segmentation, tracking) and understanding of computer vision pipelines.
• Familiarity with Flutter mobile development and ability to integrate backend/AI outputs into the app UI.
• Experience or willingness to work with OpenCV, TensorFlow or PyTorch for model development and inference.
• Good problem-solving and analytical skills, plus creativity in building intelligent user experiences.

Technologies & tools

• Languages / frameworks: Python, Flutter, any backend framework, PostgreSQL.
• CV / AI: OpenCV, TensorFlow, PyTorch; model training, inference and tracking techniques.
• Dev tools & cloud: REST APIs, GitHub, Slack, Visual Studio Code, cloud hosting (Azure).

Logistics

• Internship type: Masters, Engineer (PFE).
• Constraints: On Site, Individual (one student project).

How to apply

• Apply online: https://lnkd.in/d-PrStHN
• Or by email: Careers@feridaroundtheworld.com
• Use email subject: "PFE Internship Application - Subject #8 - AI-Powered Smart Parking Detection" when applying by email.