Collecting data on waste streams at festivals are performed manually by over-educated hands. This is both time consuming, overly expensive and logistically difficult.
The problem addresses Sustainable Development Goal #12
The Data Hat
Our solution provides festival organizers and researchers with the necessary data on waste streams. It captures an image every time a new object is introduced in the bin and analyses the image using machine learning. From this, it can determine what material type the object is and the fill level of the bin. Furthermore, it collects each bin’s location, each object’s weight, and the time of introduction in the bin.
How can Folkemødet use this?
Great question! Festival organizers can use the data to improve and optimize the festival’s waste management system for a more sustainable festival. Maybe, it turns out that waste sorting is really poor after 11 PM in a certain area. Maybe, there is extra cardboard waste during the first two days of the festival. When organizers know what is happening inside their waste bins, they actually have a chance to do something about it. Which makes more waste end up in the right place. That’s great for the festival and the environment.
Who are we?
- Studying Design Engineering at the Technical University of Denmark
- Engaged with sustainable solutions
- First time at Folkemødet
Tobias Pock-Steen Jørgensen
Marius Helmer Larsen