Solutions/Smart Infrastructure
Target Sector: Municipalities, Transit Hubs & Public Works

Smart Infrastructure

Genovaxai delivers a unified visual operating system for municipal operators, detecting crowd density shifts, transit disruptions, and infrastructural anomalies in real time.

Genovaxai Real-Time Camera Feed - FEED: CAM-SOL-SMART-INFRASTRUCTURE [SMART INFRASTRUCTURE]
STS Gantry Crane Boom [SSA Terminals]99.4%
CRANE-0145 m/min
Container Cargo Vessel [NORTHERN JUSTICE]99.2%
VESSEL-09Moored
Container Deck Stack [Tier 1-6 Intact]98.8%
STACK-04STATIC
FEED: CAM-SOL-SMART-INFRASTRUCTURE [SMART INFRASTRUCTURE]
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

Modern cities struggle with fragmented sensor silos, delayed incident responses, and poor situational awareness across transportation hubs, rail networks, and bridges.

Genovaxai Autonomous Intervention

Continuous Sub-Second Computer Vision

Genovaxai delivers a unified visual operating system for municipal operators, detecting crowd density shifts, transit disruptions, and infrastructural anomalies in real time.

End-to-End Workflow

How Smart Infrastructure Operates in Production

STAGE 01

Roadside sensors feed low-bitrate edge nodes

STAGE 02

Edge models infer local anomalies and compress metadata

STAGE 03

Telemetry synced to Civic Operations Command Dashboard

STAGE 04

First responders receive geocoded incident snapshots

Core Operational Features

  • Platform crowd density and platform edge fall detection
  • Bridge and tunnel congestion telemetry
  • Civic asset visual health monitoring
  • Emergency vehicle corridor preemption data

Technical Capabilities

  • Extreme weather resilience (fog, rain, night vision filter)
  • Cross-modal integration with acoustic sensors
  • RESTful Open Data compliance APIs
  • Scalable to 10,000+ simultaneous stream ingestion

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