Passenger counting
camera system
A complete edge AI system we engineered for transit operators — custom hardware, on-device inference, and a reporting pipeline that runs 24/7 in extreme conditions.
Counting passengers in Indian buses
Transit operators had no reliable way to audit actual ridership against ticket sales. Manual counts are inaccurate. Existing solutions weren't built for the crowding patterns, lighting conditions, and harsh environments of Indian public transit.
Trip-by-trip data for ticket reconciliation
Every boarding and alighting captured and logged. Operators audit actual ridership against ticket sales.
Fill more passengers, know exact counts
Operators can confidently fill more passengers on-route, knowing independent counts are being tracked.
Driving patterns, stop-level data, peaks
Stop-level ridership data and peak analysis to optimise routes and scheduling.
Full-stack edge AI system
Custom hardware design
Purpose-built camera unit with embedded compute. Ruggedised for heat, dust, and vibration. Day and night operation with IR capability.
On-device CV models
Person detection and tracking optimised for overhead camera angles. Handles crowding, dim lighting, and crew filtering — all inference on the edge device.
Live reporting pipeline
Real-time data upload over cellular. Trip reports with video clips for each boarding/alighting event. Cloud dashboard for fleet-level analytics.
Made for Indian transit
Trained on Indian boarding patterns — crowded doorways, simultaneous entry/exit, non-standard stops. Adapts to global markets.
If it works here, it works anywhere
Anyone can build CV for a clean, controlled environment. We made ours work in the hardest conditions — 50°C heat, dust, vibration, pitch darkness, patchy connectivity, and crowds pushing through a single door simultaneously. That's the engineering challenge we solved.
- ✓ Accurate detection in zero-light and overcrowded doorways
- ✓ On-device inference at 50°C with no active cooling
- ✓ Offline-first architecture — stores and syncs when connectivity returns
- ✓ Proven in the field, adaptable to any transit system globally
Two clips from deployed buses
The hardware and models running on live routes. No re-edits, no lab setup.
Passenger counting · full debug
Detection + part-segmentation + re-id + path tracking overlaid on the doorway feed. What the pipeline sees, frame by frame.
IR night vision · 24/7
Same pipeline, IR sensor, zero ambient light. On-device inference runs unchanged through the night shift.
Need an edge AI system?
We've proven we can go from concept to deployed hardware running real-time CV models. Let's talk about your use case.