Problem
The workflow needed rapid classification support in environments with unstable connectivity.
Constraints
- Inference latency needed to remain acceptable on-device
- Model behavior had to tolerate imperfect capture angles
- UI had to keep scan interactions simple for repeat use
System workflow
- Built a lightweight model iteration and evaluation loop.
- Implemented mobile capture and inference triggers.
- Tested the scan-and-review flow for repeated use in constrained conditions.
Result
- Delivered a demo-ready scan workflow with local inference.
- Identified clear next steps for dataset and model improvement.
- Documented architecture tradeoffs for deployment planning.
Tech stack
- Computer Vision
- Android
- TensorFlow Lite
- Mobile UX