Real-time Incident Detection
Manual monitoring of hundreds of feeds misses critical events. NTRA detects and alerts in real time.
Industry / Smart Cities
AI Surveillance for Smart Cities
Transform public infrastructure into intelligent, safer, and more efficient environments with real-time edge AI analytics — across roads, junctions, transit corridors, and crowd venues.
- Edge AI
- Data Sovereignty
- 42ms Latency
- 99% Detection Accuracy
42ms
Detection Latency
99%
Detection Accuracy
100+
Concurrent Cameras
Edge
On-Prem Processing
Challenges we solve
Crowd Management
No early warning before crowd-crush conditions form. Predict density and act before it escalates.
Traffic & Parking Visibility
Citizens lack live occupancy data. Enforcement stays reactive and inefficient.
Top use cases
Crowd Count & Estimation
Predict crowd-crush conditions 90 seconds earlier at events and transit hubs.
ANPR (License Plate)
Automated number-plate recognition for toll, parking, and zone enforcement.
Weapon Detection
Sub-second armed-threat alert routed to the control room.
Garbage & Debris
Auto-detect uncleared garbage and debris across public spaces.
Fire & Smoke Detection
Early fire and smoke alerts before major damage occurs.
How NTRA can help for Smart Cities
Edge-deployed AI vision across your existing camera fleet — tuned to your operating environment, integrated with your stack.
Person Analytics
Tracking, counting and attribute recognition across municipal feeds.
Threat Detection
Weapons, fights, intrusion and other public-safety events in real time.
Vehicle Intelligence
ANPR, traffic-flow analytics, and violation detection across corridors.
Object Monitoring
Fire, smoke, debris, and abandoned-object surveillance.
Deployment
On-prem deployment that fits your existing camera fleet
City Cameras
RTSP / IP / MJPEG
NTRA Edge AI
On-premise inference
VMS / SOC
Your control room
Your data never leaves your network.
- Plug into existing IP / RTSP cameras — no rip-and-replace required
- Edge inference on commodity GPU servers, no cloud round-trip
- Air-gapped or VPC deployment for full data sovereignty
- Integrates with VMS, SOC dashboards, and BI tools via REST and webhooks
Frequently asked questions
Does video leave our network?
No. All inference runs on-prem at the edge; only metadata (events, counts, alerts) reaches your dashboards.Can we use existing cameras?
Yes — any IP / RTSP feed at 1080p or above is supported out of the box.What infrastructure is required for edge deployment?
A commodity GPU server per cluster of roughly 100 cameras. Exact sizing is confirmed during the technical scoping call.How quickly can we go live?
Pilot deployments typically reach live monitoring within 4 weeks on existing camera fleets.
Get started
Ready to deploy AI Vision across your smart cities infrastructure?
Book a walkthrough with the NTRA solutions team.