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Edge AI Reference Architectures for Real Deployments

Last updated: April 2026

Practical deployment blueprints for edge AI systems: retail analytics, small business surveillance, smart city traffic, and warehouse safety. Each architecture includes a recommended platform, bottlenecks, and links to validate assumptions in Edge AI Stack tools.

4 architecture pages
4-16 cameras
Nano, NX, AGX
Decision-ready

Browse Architectures

Start with the scenario closest to your deployment, then use the linked calculators to adjust camera count, resolution, frame rate, storage retention, power, and model complexity.

Retail 8 Cameras Orin NX

Retail 8-Camera Edge AI

Balanced retail analytics architecture using Jetson Orin NX for 8x1080p cameras, detection, tracking, local storage, and metadata-to-cloud workflows.

Best for
Stores, boutiques, clinics, and small facilities
Main risk
Model complexity and decode headroom under sustained load
SMB 4 Cameras Budget

SMB 4-Camera Budget Build

Low-cost small business architecture using Jetson Orin Nano Super for basic detection, people counting, event alerts, and short retention windows.

Best for
Budget-conscious SMB deployments
Main risk
Overloading budget hardware with heavier models or higher FPS
Smart City 16 Cameras AGX Orin

Smart City 16-Camera Traffic AI

High-density traffic analytics architecture using Jetson AGX Orin for intersections, vehicle detection, pedestrian zones, storage, and thermal planning.

Best for
Intersections and municipal traffic analytics
Main risk
Decode, storage, thermal, and network pressure at high density
Warehouse Safety Orin NX

Warehouse Safety AI

Industrial forklift and pedestrian monitoring architecture using Jetson Orin NX with local alerts, event clips, zone rules, and safety dashboard integration.

Best for
Warehouses, loading docks, and industrial aisles
Main risk
Camera placement, occlusion, glare, and alert fatigue

Choose by Deployment Question

Validate Any Architecture

Have a deployment that does not match these?

Describe camera count, resolution, frame rate, workload, retention, and environment in the System Designer. Edge AI Stack can recommend platforms and highlight lower-cost or higher-headroom alternatives.

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