Aimed at kids, the product was officially launched on Wednesday (which was Earth Day) and the company has teamed up with a non-profit organisation called One Tree Planted, to launch this product. “For every one we sell, the customer will get to plant a tree in one of four continents across the world!” says pi-top.
What’s included in a Pod? You get the programmable Sensor Module itself, which is compatible with Grove and have a magnetic base to be easily attached to your projects. There are two wires to connect the sensors to your pi-top  computer, two LEGO connectors to easily integrate the sensors into your own creations and, finally, a “Pulp pod”, a small biodegradable, paper pulp pod that doubles as a seedling pot for growing your own fruit and veg.
The Sensor Pods cost $9.99 each and the pi-top  is priced at $299.00.
To help guide kids in projects there’s also another resource – pi-top Further, is the company’s online learning space. They write:
“You’ll find 100+ hours of fascinating projects to help you make the most of your pi-top  and Sensor Pods. Ever wondered how an ultrasonic sensor works? What is a Light Emitting Diode exactly? Further will show you step-by-step how to connect sensors, LEDs and other components, and how to write code to control them in interesting and useful ways.”
Earth Day’s theme this year is “Climate Action” and pi-top has thrown its weight behind it.
“To do this we’ve designed the product packaging to double as a biodegradable plant pot that kids and parents can use to plant their own veg. COVID-19 has made this a popular thing to do at the moment, as demonstrated by the new Marks & Spencer’s Little Garden pots.”
The company will be offering – until 29 of April – a 30% discount on pi-top  to anyone ordering the Sensor Pods.
Find out more at www.pi-top.com/pods
Ryan Dunwoody is an EW BrightSpark from the original class of 2017 we are very pleased to say. You can read his profile here.
When he was recognised as a BrightSpark he was already a successful businessman, at the age of 26, having earned a 1st Class Masters in Engineering Science from Oxford University. His areas of specialty include: electronics, robotics, machine learning and computer vision.