EuroSciPy 2026

login

Developing IoT sensors with MicroPython
.ical
2026-07-22 –, Room 1.19 (Ground Floor, Shannon)

In this workshop, you will create practical internet-connected sensors with MicroPython. We will cover the basics of setting up the development environment, both for developing on PC and deploying/developing on a microcontroller device.

Targeted towards those that are already comfortable programming in Python, but that have little exposure to embedded/hardware/electronics.

We will provide some MicroPython-capable hardware to develop against, pre-flashed with MicroPython. You may need to sit together in pairs or small groups for the on-device part.

Prerequisites

Participants must bring:

  • Laptop with Linux/MacOS/Windows
  • Have Python 3.12+ with virtualenv support installed
  • If no USB Type-A on your laptop: USB-C to USB Type A adapter

Materials: https://github.com/jonnor/micropython-iot-sensors-course

Section 1: Basics — Running in Simulator (Wokwi)

  1. Introduction — Microcontroller / MicroPython / Wokwi
  2. Analog and Digital GPIO
  3. Concurrency with Asyncio
  4. Digital Bus (I2C)
  5. Talk to Servers using HTTP Client
  6. IoT Networks using MQTT

Section 2: Running on Device (RPi Pico)

  1. Deploying on Device with mpremote
  2. Standalone IoT Device with HTTP Server and WebUI

Section 3: Running MicroPython on PC

  1. Install & Run MicroPython on Linux/macOS/Windows

Section 4: Advanced Topics (Self Study)

  1. Installing MicroPython on Device (ESP32, RP2)
  2. Efficient Code — JIT Decorators, Inline Assembler, C Modules
  3. DSP and Machine Learning with emlearn-micropython
  4. MicroPython for Embedded Linux
Expected audience expertise: Domain: none Expected audience expertise: Python: some Supporting material: Supporting material Your relationship with the presented work/project: Active contributor
The speaker’s profile picture
Jon Nordby

Jon is a Machine Learning Engineer specialized in IoT systems. He has a Master in Data Science and a Bachelor in Electronics Engineering, and has published several papers on applied Machine Learning.
He has been contributing to open-source software since 2010.

These days Jon is co-founder and Head of Data Science at Soundsensing, a leading provider of condition monitoring solutions for commercial buildings and HVAC systems.
He is also the creator and maintainer of emlearn, an open-source Machine Learning library for microcontrollers and embedded systems.

This speaker also appears in: