Our Lady of the Snows Catholic Academy – Canmore

Robots by Olots


Project Summary


SPAM OLOTS (Sustainable Plastic Autonomous Machine of Our Lady of the Snows) is the team’s solution for sorting mixed bales of plastic. Plastic recycling is a commonly known environmental issue that impacts us globally, so the team has been working on a way to encourage people to properly clean and sort their recycling through education and the use of technology. Using image recognition programming, they are working on building a robot that can successfully identify and sort type 2 plastic, which will in turn create profit locally, rather than accumulate further plastic waste.

The team has been meeting weekly at school, brainstorming, learning programming, developing their pitch through their new website and spending time on outreach. On Saturday, January 26, they held a school workshop with their mentor Eiden Yoshida, where they focused on using python to identify type 2 plastic.
The team is meeting weekly after school and continues to build their programming skills to bring a viable prototype forward to the public.


Project Summary


Last Update: July 2019.

The aim of our project is to identify plastic by type, in order to improve the recycling process. Today, as we can no longer send our plastic waste to the sorting facilities in China, we have been struggling to effectively dispose of these products. Plastic is not being properly recycled because it is contaminated, and isn’t being sorted by number. Our local town of Canmore has already invested in a 1 million dollar machine used to sort plastic, cardboard and aluminum. However, this process is not completely effective, and Canmore’s management facility has no place for these mixed plastic bales. As of now, workers in Calgary work 8 hours to “sort” plastics that commonly ends up in landfills, while we continue to work at a loss, paying companies to dispose of our plastics. Our minimum viable prototype uses Computer Vision, a trained model that uses various amounts of photographs to identify plastic in a controlled setting.
We recognize the incorporation of Computer Vision to help us initiate the construction of our prototype. We would like to test our project in the public, as well as add a mechanism to feed plastic autonomously into the machine. With the help of our mentors, we collectively came up with several drafts of a machine, before eventually deciding on a working model. We have now come back to and changed bi-weekly and taken many pictures to train the Computer Vision model. Our prototype is able to detect and sort the type 2 plastic from the other types of plastic. And we had decided to sort type 2, because it is the most profitable from all the types if it is properly sorted. This is a brief summary about our project, and we will see you at the jamboree and tell you more about our project and see our prototype or you can visit our website for regular updates.