Raspberry Pi Awards 2023: Years 10-11 Finalists

This year, we challenged students to develop ingenious solutions in response to the theme: accelerating energy transition.

Out of the many innovative submissions by teams around the country, here are the finalist projects from years 10-11 students:

Carbon Seeker from Dollar Academy

Reducing your carbon footprint

Carbon Seeker allows individuals to make informed decisions about their home appliances' environmental impact, learn about their carbon footprint, and identify ways to reduce it. By simply entering the brand and product name, users can choose between a quick scan or a long scan. The quick scan option provides users with quick and accurate information, while the long scan searches the entire internet for data about the product, providing users with more comprehensive results.

Pi Stars from SEK Dublin International School

Reducing food wastage

The main purpose of this project is to reduce the amount of food wasted at any venue. The product takes an image of the consumable with the best before date on it. It then converts the date into text for the Raspberry-Pi to read using optical character recognition. The system will find the difference between the best before date and the current date to find out when the product will expire. An e-mail will be sent to the user's email account to notify them.

SOLA from The Liverpool Blue Coat School

Improving the efficiency of solar panels

Our project aims to improve the efficiency of solar panels in both domestic and industrial contexts. We achieve this by calculating the optimum angle(s) that the panel should be fixed at throughout the day using hyper-sensitive phototransistors which are rotated by two stepper motors. This meets a real consumer need apparent in the solar panel industry as shown by a recent study carried out by the government. The study shows that houses with well-sited solar panels can save £140 per year. Our project would be able to be implemented into people’s homes or into factories without any changes needing to be made.

Team EV from Winchester College

Planning the optimal EV charging locations

We developed a program which allows any company, city planner, architect, environmental expert and more, to more accurately plan suitable EV charging locations. To determine optimal placement, we wrote a machine learning algorithm that simulated traffic based on government data. We then calculated the profit for each charger and then found the optimal configuration of chargers to maximise profitability.

Thorium from King Edward VI Grammar School

Reducing costs and emissions from lighting

Introducing Filament, a new way of monitoring your light usage. Filament will be able to detect the artificial light coming from your household lighting and provide easy to read data to show when you have been wasting energy. Filament can be accessed from a web app or mobile app which will provide up to date statistics on your total spendings and allow for you to track up to date costs on household lighting with the help of a Raspberry Pi.

Wasted Water from Stonelaw high school

Managing water usage effectively

We have created a drain turbine that will display the amount of water that is wasted throughout households and businesses. This turbine can be installed into pipes and as water flows down the drains, it will spin our turbine which will be linked to a rotary encoder. The data from the encoder will then be displayed on our application, Wasted Water, where you can view the amount of water used that day and access records from previous days.