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<div class="csl-entry">Taurer, F., Wolling, F., Moore, J., & Michahelles, F. (2023). Smart Trash Can: Easy Collection of Photos of Organic Waste in the Home. In <i>MUM ’23: Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia</i> (pp. 571–573). Association for Computing Machinery. https://doi.org/10.1145/3626705.3631881</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/190641
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dc.description.abstract
The recycling of organic waste through composting or fermentation is an easy yet underestimated way to bind CO2. Due to a lack of awareness, society is still insufficiently separating recyclable organic waste from unsuitable residual waste. Any impurities inevitably reduce the quality of a single container and, thus, the entire load of a waste transporter, resulting in its expensive and less sustainable energy recovery through incineration. To prevent the addition of impurities and the inevitable incineration of valuable organic waste, the problem must be tackled directly at the producer’s site. In the context of a preliminary experimental study, a Smart Trash Can has been developed to automatically take photos of the waste each time it is filled. It serves as a convenient means to collect a series of photos that will contribute to a large dataset for the training of machine-learning models to assess and monitor waste quality. In this way, not only can contaminated waste be separated from pure organic waste, but also feedback, incentives, or nudges can be provided to the user to lead to better waste separation.
en
dc.language.iso
en
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dc.subject
impurity detection
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dc.subject
organic waste
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dc.subject
dataset
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dc.subject
data collection
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dc.subject
in-the-wild study
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dc.subject
sustainability
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dc.title
Smart Trash Can: Easy Collection of Photos of Organic Waste in the Home
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dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
St. Pölten University of Applied Sciences, Austria