Selected Work
AI Carbon Tracking
A TÜBİTAK 2209-A project exploring AI-assisted mobile micro-interactions for individual carbon-footprint tracking.
Overview
A TÜBİTAK 2209-A funded project exploring AI-assisted mobile micro-interactions for individual carbon-footprint tracking.
What we built
- Authentication and a mobile home flow.
- Transportation activity entry and habit/profile collection.
- Food and image-upload workflows.
- A Node/Express backend, FastAPI AI service and Firebase integration.
- AI-assisted food and product analysis experiments.
Technical structure
The mobile client works with Node/Express services and Firebase, while a FastAPI service supports the AI-assisted analysis experiments. The work keeps daily input flows lightweight while leaving the AI layer separate from the main application backend.
Current state
Active final-stage project work focused on the implemented mobile, backend, Firebase and AI-assisted flows. Not every target in the original proposal is represented as completed work.
Lessons learned
- Mobile interaction design needs to make frequent tracking feel lightweight.
- Separating the application backend from AI experiments keeps integration work easier to reason about.
- Proposal scope and implemented work need to remain clearly distinguished.
Research Proposal
The original TÜBİTAK 2209-A proposal describes the research goals, planned interaction model, methodology and evaluation approach.
Open proposal