Build a Privacy-First LLM Smart Home on Raspberry Pi 5

About this Learning Path

Who is this for?

This is an introductory topic for edge AI developers, Raspberry Pi hobbyists, and software engineers who want to build privacy-first smart home assistants. You’ll learn how to run large language models (LLMs) locally on the Raspberry Pi 5 using Ollama, control GPIO-connected devices, and deploy a web-based assistant without relying on cloud services.

What will you learn?

Upon completion of this Learning Path, you will be able to:

• Understand how the Arm architecture enables efficient, private, and responsive LLM inference
• Run a smart home assistant on Raspberry Pi 5 with local LLM integration
• Wire and control physical devices (for example, LEDs) using Raspberry Pi GPIO pins
• Deploy and interact with a local language model using Ollama
• Launch and access a web-based dashboard for device control

Prerequisites

Before starting, you will need the following:

• An Arm-based single board computer (for example, Raspberry Pi 5 running Raspberry Pi OS)
• Electronic components (breadboard, LEDs, resistors, jumper wires) for GPIO testing
• Familiarity with Python programming, Raspberry Pi GPIO pinout, and basic electronics