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AutoEye

Platform Users — Engineers & Low-code Ops Users (ORA / Panel Builder) OR Platform ORA — AI Planning Interface Agent Workflows Plan Visualisation ADK Integration SDK UI — Frontend Shell FDK Architecture Low code Config-driven DDK Schema Definition Code Generator Generated Server MDK WEM DAL Experiment Manager Nexus Deployment Control Live Monitoring Registry Browser SCDK Source Control Pipeline Mgmt Azure DevOps deploys ↓ SDK API — GraphQL Federation Gateway Federation Gateway Component Resolvers Auth & Licensing Plugins: gql-autogeneration Migrator Helm KinD Boilerplate GenAI ··· Microservices — Domain IP Services Data Pipeline Core Platform Metrics & Analytics Spatial & Geo Simulation Event Detection Camera & Device Fire & Resource Opt. Satellite Modelling ↓ Nexus deploys Deployed OR Applications Rail Ops Dashboard Mine Mgmt Dashboard Port Ops Dashboard ··· FDK-built · DDK-backed · MDK-powered · deployed via Nexus ↑ Application Users — Operations Teams (shift managers, analysts, planners)

Overview

AutoEye is a cloud-based computer vision platform for processing traffic camera video streams. It provides capabilities to develop and deploy computer vision use cases across camera networks, starting with vehicle counting and detection, and designed to scale to thousands of camera streams.

The platform processes live video feeds using GPU-accelerated compute, running object detection, tracking, and analysis pipelines. Results are aggregated and made available to the platform for use in metrics calculation, event detection, and operational dashboards.

User documentation for Optimal Reality