Cutting traffic-violation processing from 90 seconds to 10
An AI violation-detection and number-plate OCR pipeline built with Hyderabad Traffic Police, cutting per-challan processing time by 89% in the Jubilee Hills pilot.
- 1,125
- Images captured
- 206
- Challans generated
- 89%
- Faster processing
The challenge
Issuing a traffic challan from a field photograph was an operator-driven task: read the number plate, identify the violation, look the vehicle up against RTA records, then raise the challan. At roughly 90 seconds per case, throughput was capped by how many operators were at desks.
What we built
Smart Traffic AI detects violations directly from field images and reads number plates with OCR, cross-checking each against RTA records and attaching a confidence score. Verified cases are pushed to an operator dashboard where a human approves or rejects rather than transcribes.
Field officers work through a mobile app built for real conditions, including offline sync for areas with unreliable connectivity.
- AI-based violation detection and number-plate OCR
- RTA cross-check with per-case confidence scoring
- Mobile app for field officers, with offline sync
- Operator dashboard for review and approval
The outcome
In the Jubilee Hills pilot the system captured 1,125 images and generated 206 challans. Per-case processing fell from about 90 seconds to about 10 — an 89% reduction — with operators moving from data entry to verification.