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.
// Edge AI Decision Platform
Design your edge AI deployment. Compute, storage, power, bandwidth, and cost — sized together.
Input your cameras, model, and constraints. Get a recommended platform, resource utilization, bottleneck analysis, and a BOM your procurement team can use. Now supports single-node, multi-node, and edge server architectures. Vendor-neutral.
// Start here
FLAGSHIP TOOL
Design a Full Deployment
Complete deployment analysis: platform selection, compute sizing, storage, network, power, and cost.
Now supports single-node, multi-node, and edge server architectures.
Open System Designer →
STEP-BY-STEP
Guided System Design
Answer 8 simple questions about your deployment. Get an instant architecture recommendation
with a direct link to the full System Designer.
Start Guided Design →
COST PLANNING
Estimate Deployment Cost
Compute + storage + power + network + enclosure → itemized BOM with
cost-per-camera breakdown. Share with procurement or export as JSON.
Estimate Cost →
// Reference Architectures
Start with a proven edge AI deployment
Reference architectures for real-world camera AI systems — with recommended hardware, bottlenecks, power, storage, bandwidth, and direct links back to EdgeAIStack calculators.
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.
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.
Warehouse Safety AI
Industrial forklift and pedestrian monitoring architecture using Jetson Orin NX with local alerts, event clips, zone rules, and safety dashboard integration.
Not sure where to start?
I need the lowest-cost setupSMB 4-Camera Budget Build
I have a retail storeRetail 8-Camera Edge AI
I have 16 cameras or mixed 4KSmart City 16-Camera Traffic AI
I need low-latency safety alertsWarehouse Safety AI
// Bottleneck Workbench — live preview
INCLUDED IN SYSTEM DESIGNER
What breaks first when you
double the cameras?
After every recommendation, push the limits. Double cameras, switch codecs, change models — see compute, memory, power, and storage shift in real time. Find the bottleneck before you buy the hardware.
- Live compute, memory, power, network, and storage gauges
- One-click stress scenarios — 2× cameras, worst case, H.265
- Baseline vs modified comparison
- Engine-validated with confidence scoring
BOTTLENECK WORKBENCH
// Decisions teams use EdgeAIStack for
// Hardware
What hardware do I need?
Input cameras, model, and constraints — get a recommended platform with confidence scoring.
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// Scaling
What breaks if I scale up?
Double cameras, change codecs, switch models — see exactly which resource hits the wall first.
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// Architecture
Single node or multi-node?
See whether your workload fits one edge node, multiple embedded nodes, or a centralized edge server.
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// Storage
How much storage for 30 days?
Camera count, resolution, codec, retention — get exact TB and drive lifespan.
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// Cost
What's the total deployment cost?
Compute + storage + power + network + enclosure → itemized BOM with cost per camera.
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// Compare
Compare platforms side by side
Orin Nano vs NX vs AGX — throughput, power, cost, and headroom for your specific workload.
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// Platform Catalog — 10 embedded platforms indexed
Jetson Orin Nano Super
Compute67 TOPS
Power10–25W
Max Streams8× 1080p
Est. Cost~$249
Jetson Orin NX 16GB
Compute157 TOPS
Power10–40W
Max Streams18× 1080p
Est. Cost~$599
Jetson AGX Orin 64GB
Compute275 TOPS
Power15–60W
Max Streams40× 1080p
Est. Cost~$1,599
Jetson Thor T5000
Compute2,070 TOPS
Power40–130W
Max Streams60× 1080p
Est. Cost~$3,499
Google Coral Edge TPU
Compute4 TOPS
Power2–2.5W
Max Streams3× 1080p
Est. Cost~$60
Rockchip RK3588 NPU
Compute6 TOPS
Power5–20W
Max Streams6× 1080p
Est. Cost~$149
// Start with your deployment type
// Retail
Retail Analytics
Single-camera classification. Checkout recognition, footfall counting.
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// Manufacturing
Industrial Inspection
High-accuracy defect detection. Fanless, extended temperature range.
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// Smart City
Traffic Monitoring
Multi-stream semantic segmentation. Outdoor, high-throughput deployments.
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// Robotics
Autonomous Systems
Pose estimation + multi-model pipelines. ROS2, mobile power constraints.
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// Agriculture
Remote AI Sensors
Battery-powered, fanless inference. Intermittent connectivity.
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// Security
Surveillance
24/7 multi-stream detection. High throughput, storage-intensive.
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// Agent-Native Architecture
Any AI assistant can call these engines.
EdgeAIStack exposes all sizing engines as tool calls. MCP server for Claude, Cursor, and Windsurf. OpenAPI spec for GPTs and custom agents. One API call runs 8 engines in parallel and returns a complete deployment specification with confidence scores.
MCP
Model Context Protocol — 6 tools
OPENAPI
OpenAPI 3.1 spec — REST endpoints
RAG
2,721 vectors — engine + research layers
// MCP tool call
design_system
{
"tool": "design_system",
"input": {
"model": "yolov8n",
"camera_count": 8,
"resolution": "1080p",
"retention_days": 30,
"optimize_for": "balanced"
}
}
// Featured Guides
01
Orin Nano vs Orin NX — which should you buy?
Side-by-side comparison for real deployment workloads.
02
How much power does Jetson actually draw?
Idle, throttled, and full-load measurements across power modes.
03
PoE switch sizing for 8 AI cameras
Port allocation, power budget, and switch recommendations.
04
Best SSD for 24/7 edge recording
TBW ratings, endurance testing, and drive selection for continuous write.
05
Can you run edge AI fanless?
When passive cooling works, when it doesn't, and how to decide.
06
Storage layout for continuous recording
Ring buffers, retention sizing, and write patterns for edge deployments.
Still researching?
The engines give you answers. The guides give you context — Jetson power modes, storage endurance, PoE budgeting, thermal constraints, and deployment checklists. Start with the hardware guide or browse all 35+ engineering guides.
Prefer starting from a real system?
Browse deployment-ready edge AI blueprints, then adjust the assumptions in EdgeAIStack's calculators and System Designer.