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Edge-AI and RF bench

A Raspberry Pi 5 with a Hailo-8 accelerator, software-defined radio, and a pile of sensors — a bench for learning edge inference and RF.

edge-airaspberry-pisdrelectronicsmqtt

Diagram of a Raspberry Pi 5 plus Hailo-8 board surrounded by SDR, microcontroller, GPS, audio, and sensor components

A corner of the lab is given over to small hardware: somewhere to learn edge inference, software-defined radio, and sensor plumbing without a rack in sight.

The core

A Raspberry Pi 5 paired with a Hailo-8 AI accelerator (26 TOPS) on NVMe — enough to run real inference at the edge instead of shipping every frame back to a server.

Around it

  • Software-defined radio — a PlutoSDR and a LibreSDR, for poking at the RF spectrum and learning how radios actually work.
  • Microcontrollers — ESP32 and Raspberry Pi Pico W nodes that publish over MQTT.
  • Sensing — GPS, I²S audio, and the same pH / EC / water-level probes that feed the hydroponics side of the house.

Why

It’s the maker version of the security habit: take something you don’t understand — a radio, a tensor accelerator, a noisy analog sensor — and keep poking until you do. Most of it talks MQTT back to the home lab, which is where the data eventually lands.