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Traffic Enforcement

Enforcement

The Linker VLM Traffic Enforcement Platform is an automated violation detection and evidence-capture system. Using real-time AI object detection combined with Vision-Language Model (VLM) semantic verification, it upgrades existing street cameras into a 24×7 AI enforcement system. The system analyses road imagery continuously. AI first detects candidate violations; a second VLM layer then verifies each event semantically, filtering out false positives before the case is queued for officer review — improving both enforcement throughput and evidence quality. The platform covers multiple violation types and integrates with the agency's existing case management workflow. The same GPU, camera and AI infrastructure can further extend to flooding, potholes, litter, incidents, traffic congestion and other city AI applications.

VLM output

A fixed CCTV camera overlooks a wide urban intersection where the near-side signal heads are red and two cars (a white sedan and a silver SUV) wait inside the marked stop area at the bottom right. Over the four frames several dark sedans move laterally across the intersection on the cross street, and by the last frame the intersection has largely cleared while the near approach still holds at red.

  • Traffic Signal StateRed
  • Red-Light Violation DetectedNo
  • Vehicles Crossing Stop Line On Red0
  • Vehicles Stopped At Stop Line2
  • Crosswalk Blocked By VehicleNo
  • Pedestrians In CrosswalkNo
  • Wrong-Way Or Illegal TurnNo
  • Moving Vehicles In Intersection1-3
  • License Plate LegibilityLow

Customer challenges

1

High deployment cost: traditional systems run approximately US$80K per intersection, with each additional violation type priced separately — city-wide rollout is fiscally prohibitive.

2

Capability limited by hardware: detection runs as edge AI inside the field equipment and is tied to its specification, so each additional violation type must be purchased (about US$15,600 per site) and may require equipment changes and recalibration.

3

False positives consume manpower: rule-based detection produces false alerts that officers must screen case by case, and drives public appeals.

4

Camera drift goes unnoticed: pole displacement or impact shifts the field of view; this is typically discovered after the fact and requires an on-site crew to recalibrate.

5

Technology stagnation: under capital-purchase contracts, detection models are no longer updated after handover.

Customer benefits

One camera covers 10 violation types — no dedicated equipment needed for each

New violation types are a software upgrade, with no construction work required

24×7 continuous analysis, no coverage gaps

Open camera specification — no vendor lock-in

Case-by-case verification before citation; AI filters false positives, sharply reducing officer review workload

Automatic determination of statutory reference lines (e.g. the 3-metre crosswalk boundary)

Evidence packages generated automatically in the required regulatory format

Direct integration with police systems — officer workflow remains unchanged

Deploys on the agency's existing sovereign AI compute, or on sovereign cloud or private cloud infrastructure that meets data residency requirements

Video stays in the municipal data centre, keeping privacy and security accountability clear

Existing enforcement sites and compute resources are reused, lowering deployment cost

The same compute can later extend to flooding, potholes, incident detection and congestion

Key features

A single licence covers the following 10 violation types, detected simultaneously by one camera:

One licence enables simultaneous detection of the ten violation types listed below from a single camera.

Red-light running

Detects vehicles running a red light.

Failure to yield to pedestrians

Detects vehicles failing to yield to pedestrians.

Illegal left and right turns

Detects illegal left and right turns.

Failure to obey signs, road markings and signals

Detects failure to obey signs, road markings, and signals.

Crossing double white lines / illegal lane changes

Detects crossing of double white lines and illegal lane changes.

Parking on red and yellow lines

Detects parking on red and yellow lines.

Wrong-way driving

Detects wrong-way driving.

Motorcycles failing to perform the required two-stage left turn

Detects motorcycles failing to perform the required two-stage left turn.

Obstructing crosswalks and motorcycle waiting zones

Detects vehicles obstructing crosswalks and motorcycle waiting zones.

Improper lane use (heavy vehicles, motorcycle lanes)

Detects improper lane use by heavy vehicles and in motorcycle lanes.

Before & after

Before Detection runs on edge AI built into the field equipment; the violation types it can catch are fixed at purchase, typically 1–2. After — with Linker AI Nexa Detection runs on data-centre GPUs; one camera covers 10 violation types simultaneously.
Before Each additional violation type costs about US$15,600 per site and may require equipment changes and recalibration. After — with Linker AI Nexa Each additional violation type is a software update at US$625 per site/year, with no field equipment changes.
Before Approximately US$8,100 per violation type per site per year (buyout price amortised over five years, based on 2 types). After — with Linker AI Nexa US$940 per violation type per site per year — about one ninth of the traditional cost.
Before Deploying 10 violation types across 150 sites costs about US$33.3M to build, before maintenance and network. After — with Linker AI Nexa Five-year TCO across 150 sites is about US$8.5M, including hardware, network and licence.
Before Officers screen every false alert, and camera drift is usually discovered only after the fact. After — with Linker AI Nexa The model verifies each case before citation, and field of view is detected and recalibrated automatically.
Before Compute is tied to the field equipment and serves only that project. After — with Linker AI Nexa Deploys on the agency's sovereign AI compute, sovereign cloud or private cloud, and is shared across city applications.
Before The system is single-purpose and cannot be extended beyond enforcement. After — with Linker AI Nexa The same camera and GPU infrastructure extends to flooding, potholes, litter, incident detection and traffic congestion.