Solutions/Traffic Intelligence
Target Sector: Highways, Tollways & Urban Transit

Traffic Intelligence

Genovax Traffic converts existing highway cameras into real-time traffic flow sensors, detecting stopped vehicles, debris, and lane violations within seconds.

Genovaxai Real-Time Camera Feed - FEED: CAM-SOL-TRAFFIC [TRAFFIC INTELLIGENCE]
Heavy Commercial Hauler [Lane 2]99.5%
TRK-90262 km/h
Passenger Sedan [Headway Margin 42m]99.2%
CAR-41168 km/h
FEED: CAM-SOL-TRAFFIC [TRAFFIC INTELLIGENCE]
RES: 2560x1440 @ 60 FPSFPS: 60.0INT8: 5.8msms
GENOVAXAI:GENOVAXAI: TENSORRT ENGINE ACTIVE
Classified TargetTelemetry MonitoredBoundary Alert
GENOVAXAI INDUSTRIAL STREAM
The Industry Operational Challenge

Manual Blind Spots & Delayed Alerts

Traffic congestion causes billions in lost economic productivity and increased emergency response delays on unmonitored road segments.

Genovaxai Autonomous Intervention

Continuous Sub-Second Computer Vision

Genovax Traffic converts existing highway cameras into real-time traffic flow sensors, detecting stopped vehicles, debris, and lane violations within seconds.

End-to-End Workflow

How Traffic Intelligence Operates in Production

STAGE 01

High-speed highway camera streams fed via fiber network

STAGE 02

High-framerate detector counts and tracks vehicles across lines

STAGE 03

Velocity computed via calibrated virtual trigger loops

STAGE 04

Incidents pushed directly to dynamic roadside message signs

Core Operational Features

  • Automated stalled vehicle & debris detection on lanes
  • Vehicle classification and axle estimate detection
  • Average speed and flow-rate calculations
  • High-occupancy toll (HOT) lane compliance audit

Technical Capabilities

  • Speeds up to 140 mph (225 km/h) tracking accuracy
  • Night illumination headlight glare filtering
  • Standard NTCIP protocol support for DOTs
  • Multi-lane simultaneous tracking (up to 8 lanes)

Underlying GPU Pipeline Architecture

8-Stage End-to-End Visual Processing Pipeline

Zero-Memory-Copy Accelerated Architecture

TOTAL PIPELINE LATENCY:< 11.1ms
LAYER 04Neural Backbone
Active Production

Computer Vision Pipeline

Extracts high-dimensional spatial feature representations across industrial machinery, workers, gear, vehicles, and hazardous boundaries.

Engineered Specifications:
  • Dual-backbone feature pyramid networks for micro-object detection
  • Pose keypoint extraction for ergonomics and slip-and-fall alarms
  • Multi-head classification for sub-category asset discrimination
TARGET PLATFORM:YOLOv10 / RT-DETR / Spatial Vision Transformers
STAGE LATENCY:< 3.2 ms