Aforix
Real-time space occupancy classification with computer vision
Computer VisionTensorFlow.jsTeachable MachineNext.jsReal-timeB2B
Aforix
Aforix is a computer-vision system that classifies the real-time occupancy level of physical spaces — empty, partial, full — and turns that into actionable alerts and operational intelligence for staffing decisions.
The problem
Health and financial-service companies assign personnel manually or by intuition, producing long waits at peak hours and idle staff in quiet windows.
The approach
| Layer | Choice |
|---|---|
| Camera | IP cameras, frame capture every 10–30s |
| Model | Trained in Teachable Machine, exported to TensorFlow.js |
| Backend | Next.js + Postgres + alerting webhooks |
| Dashboard | Real-time tiles per branch and historical reports |
Designed for healthcare (waiting rooms), banking (teller queues), and government services (citizen-care offices). The classification ladder maps directly to recommended actions for the operator on duty.
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