Warehousing / Logistics / Computer Vision
AI Warehouse Camera Pallet and Forklift Counting System




Student Project Brief
AI Warehouse Camera Pallet and Forklift Counting System
Use camera feeds, ROI zones, motion detection, and event records to build an AI counting dashboard for pallet movement, forklift activity, exceptions, and review status.
Real Business Problem
Warehouses need to track pallet, forklift, and box movement, but manual camera review is slow and event records are easy to miss.
AI Solution
Use camera feeds, ROI zones, motion detection, and event records to build an AI counting dashboard for pallet movement, forklift activity, exceptions, and review status.
Application Story Angle
This project helps students explain how they understood a real industry problem, turned AI from a tool into a solution, took a role in a team, and delivered evidence they can show.
Portfolio Deliverable Examples
- One-page project brief
- Feature flow or UI prototype
- Testing records and before/after improvements
- English Demo Day presentation
Best For
- G9-G12 students
- Students who want to present a real project in English
- Students interested in AI applications, product design, data, or business problems
Student Tasks
- Research the real industry context and user needs
- Organize sample data, content, or business workflows
- Design AI features and interface prototypes
- Test output quality and record improvements
- Present the project and demo in English
Student Roles
- AI Engineer
- QA Tester
- Data Analyst
- Content & Marketing
- Project Lead
6-Month Participation Path
- Month 1: Business research and problem definition
- Month 2: Prototype and Demo V0.1
- Month 3: Core AI feature build
- Month 4: User testing and optimization
- Month 5: Pilot and project packaging
- Month 6: Final delivery and Demo Day
Final Evidence Package
- Working system demo
- Project report PDF
- 2-3 minute demo video
- GitHub/task records
- Business or mentor feedback
Verification Evidence
- Business feedback
- Mentor process records
- Project acceptance notes
- Student contribution statement