A new smart compost bin could help researchers track and quantify the food waste produced by households.
It’s estimated that the US alone wastes more than $400bn worth of food every year, while the UK produced around 9.5 million tonnes of food waste in 2018.
As well as being inefficient in economic terms, food waste produces significant amounts of methane and CO2 globally, contributing to climate change.
As part of the UN’s sustainability goals, the UK government has committed to halving the UK’s per capita food waste by 2030.
One issue in all countries attempting to cut their food waste is accurately assessing the food waste produced by individual households.
As Patrick Donnelly, assistant professor of computer science at Oregon State University, says: “You can’t manage what you don’t measure.”
Donnelly, who is heading the project to create the smart bin, said that food waste is tracked and measured through every other part of the agricultural food chain.
Once it comes to measuring ‘post-consumer food waste’, however, available methods are time-intensive, expensive, prone to error and impractical at large scale.
Compost bin asks for a description and takes its own measurements
The system that the researchers are developing is centred on the type of compost bin commonly distributed by waste utility companies in the US.
The user is prompted to describe the food waste – both edible and non-edible – that they deposit in the bin.
Their description is transcribed using automatic voice recognition technology, while the bin also weighs the waste deposited and collects 3D images and sensor measurements.
This enables the collection of a novel dataset that will, according to Donnelly, allow future researchers to bring computer vision to bear on the problem of food waste.
This research has received $640,000 (£505,000) in funding and is supported by the Foundation for Food & Agriculture Research and the Kroger Co. Zero Hunger Zero Waste Foundation.
The project will incorporate a pilot study, which is likely to start next spring, with volunteers helping to test the technology.
Current studies of household food waste generally rely on participants manually weighing their food waste and recording measurements in a journal.
The smart bin would automate this process, making it easier and less prone to human error.
Donnelly said that personalised data could inspire consumers to reflect on their food waste and change their behaviours over time.
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