Mini Prediction Machines

We had already worked with artist Rachel Jacobs on her ‘The Prediction Machine’: an interactive artwork which aims to engage the public with climate change issues via a fortune telling. She wanted to take the concept into the classroom and get students of all ages to get hands-on with the data.

Solution

We worked in close collaboration with Rachel to design the Mini Prediction Unit. The specifications were developed in collaboration with Rachel.

The final design comprised of two units:

Sensor unit

This was based upon the Arduino Nano and has an on-board lithium ion battery which is recharged by a small solar PV cell.

This took readings from a wind vane, an anemometer, a rain gauge, a rain sensor and a temperature sensor. This data was collected and set wirelessly (via a 433 MHz serial connection) to the display units.

Only one sensor unit was required, as all the display units receive the same data, which was sent every 15 seconds.

Display unit

This received data from the sensor unit and talked to a cloud-based timestreams client to give a prediction on a small display on the unit.

The device is based upon the ESP8266 wifi system-on-a-chip and had a small OLED display, an RGB led for indicating status, a 433 MHz wireless serial link and a couple of user input switches. It was powered via a USB connector, but all data was performed through the wifi and wireless serial link.

The units were designed to be put together by the attendees of the workshop, but we soldered the units to help speed up the workshop interaction time.

These workshops were run over a period of two months at the end of 2018 with students from a secondary school and makers from the ‘Men in Sheds‘ local group.

The software for both the sensor unit and the ESP8266 display unit is available here:

https://github.com/matthewg42/MiniPredictionMachines

The PCB design files for both boards are available here:

https://github.com/re-innovation/MiniPredictionMachine