Edge AI Stack
Edge AI Stack covers the hardware, infrastructure, and deployment decisions that matter when running AI workloads at the edge — on cameras, gateways, industrial nodes, and on-premise servers where power budgets, thermal limits, storage endurance, and total cost determine what actually ships and stays running.
What You'll Find Here
- Hardware comparisons across accelerators and platforms (Jetson, Coral TPU, Hailo, RK3588, and more)
- Deployment guides for cameras, PoE infrastructure, and edge networking
- Storage and endurance analysis — NVMe, eMMC, TBW ratings, and write amplification at the edge
- Power and thermal design — UPS sizing, fanless enclosures, and heat dissipation strategies
- Checklists and reference architectures for repeatable edge AI deployments
Start Here
Latest Guides
- PoE Camera Setup for Edge AI: Networking and Power Guide
- Fanless Enclosures for Edge AI: Thermal Design and Selection
- ONNX vs TensorRT for Edge Inference: A Practical Comparison
- UPS Sizing for Always-On Edge AI Nodes
- Raspberry Pi 5 for Edge AI: Benchmarks and Realistic Limits
- Hailo-8 M.2 Module: Throughput, Power, and Integration Notes
- Fleet Management for Distributed Edge AI Deployments