Most of the stuff I write here somehow relates to coding in Python, Raspberry Pi projects and data stuff. Enjoy!
If you invest in cryptocurrencies such as Bitcoin and Ethereum and pay tax in Germany, some day you might find yourself having to calculate how much you owe the Finanzamt. That day came for me this year and here’s how I worked it out with Python. ...
This is part of a series on my ambient data logging and visualisation setup. I’ve already given an overview of the entire architecture, and written about setting up the Raspberry Pico(s) as sensor devices. Now I’m going to explain how I collect that data in a CSV and Postgres database. Dumb sensors The sensors themselves are designed to be quite dumb. They don’t log data locally because it’s easier to access it if it’s stored centrally....
In this previous post, I gave an overview of how I collect ambient data using a Raspberry Pi and a couple of Raspberry Pico Ws. Now I’m going to go into more detail on how to set up the Pico to take readings on demand via the network. Equipment If you want to try this at home, you’ll need: A Raspberry Pico W with MicroPython installed A soldering iron and paraphernalia (or another way of connecting the sensor to the Pico W such as breadboard and jumpers) A DHT-22 or BME280 sensor A wifi network Attaching a sensor to your Pico W The MicroPython code I wrote has support for two sensors: the DHT-22 or the BME280....
The Raspberry Pico W is a cheap microcontroller (around €8) that can control sensors and access a WIFI network. With a bit of soldering and MicroPython, you can have the Pico serving ambient data in JSON format over your local network, then log it with a database and visualise it in a dashboard. Here I’m just going to briefly describe my setup as the basis for later blog articles. Overall setup Architecture diagram...