Horizon Education
Horizon Education
Tunisie

Subject #8 AI-Powered Smart Parking Detection PFE

Computer Vision (CLIP/BLIP)Mobile Development (Flutter)Backend engineering

Publié il y a environ 12 heures

Stage
⏱️4-6 mois
💼Présentiel
📅Expire dans 13 jours
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Description du poste

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.