A way to minimise contamination in home recycling

A Dyson Award entry aims to improve the efficacy of recycling with a design that identifies unrecyclable materials

Spotted: It is estimated that, in the UK alone, around 500,000 tonnes of household recycling was rejected at the point of sorting, equating to over £48 million per year in additional costs. This is largely due to contamination from non-recyclable items ending up in the wrong bin. Now, a team of students from Rice University is working to remedy this with their entry in this year’s James Dyson Award competition — the Racoon.

The students designed the system to run using a Raspberry Pi and Arduino. Users place the rubbish in an intake area, which trips a camera to image the rubbish. This is then fed to an on-board classification algorithm. Recyclables can then be sorted into the recycling bin, while non-recyclables are rejected, prompting the user to place them in an alternative bin.

Although there are other sorting bins like this available, the Rice students argue that none of them provide any incentive or feedback to users about non-recyclable items. This ultimately doesn’t solve the problem, because these bins fail to educate users on the need to sort rubbish properly. According to the team, “By failing to educate the user, the contamination problem will continue to be a major concern”.

The team was inspired to develop the device by Rice University’s own recycling programme. The university receives payment for the recycling that they deliver to the local waste management facility. However, if too many non-recyclable items are included, the load can be rejected, resulting in loss of payment and a fine. The team claims that “Our device will remove potential contaminants from the recycling stream, which will allow Rice to be more sustainable by reducing the amount of loads that are rejected.”

While these students are working to educate individual users on the need to sort, a number of other innovators are working on larger-scale systems to reduce the problem of recycling contamination. Springwise has recently covered a device that uses AI to autonomously sort and transform waste into usable materials and a Ugandan project that recycles plastic waste into construction materials. 

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