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KI-Waste - Combining Image Recognition and Time Series Analysis in Refuse Sorting

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dc.contributor.authorGursch, Heimo
dc.contributor.authorGanster, Harald
dc.contributor.authorRinnhofer, Alfred
dc.contributor.authorWaltner, Georg
dc.contributor.authorPayer, Christian
dc.contributor.authorOberwinkler, Christian
dc.contributor.authorMeisenbichler, Reinhard
dc.contributor.authorKern, Roman
dc.contributor.editorWienrich, Carolin
dc.contributor.editorWintersberger, Philipp
dc.contributor.editorWeyers, Benjamin
dc.date.accessioned2021-09-05T18:56:33Z
dc.date.available2021-09-05T18:56:33Z
dc.date.issued2021
dc.description.abstractRefuse sorting is a key technology to increase the recycling rate and reduce the growths of landfills worldwide. The project KI-Waste combines image recognition with time series analysis to monitor and optimise processes in sorting facilities. The image recognition captures the refuse category distribution and particle size of the refuse streams in the sorting facility. The time series analysis focuses on insights derived from machine parameters and sensor values. The combination of results from the image recognition and the time series analysis creates a new holistic view of the complete sorting process and the performance of a sorting facility. This is the basis for comprehensive monitoring, data-driven optimisations, and performance evaluations supporting workers in sorting facilities. Digital solutions allowing the workers to monitor the sorting process remotely are very desirable since the working conditions in sorting facilities are potentially harmful due to dust, bacteria, and fungal spores. Furthermore, the introduction of objective sorting performance measures enables workers to make informed decisions to improve the sorting parameters and react quicker to changes in the refuse composition. This work describes ideas and objectives of the KI-Waste project, summarises techniques and approaches used in KI-Waste, gives preliminary findings, and closes with an outlook on future work.en
dc.identifier.doi10.18420/muc2021-mci-ws04-373
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37354
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2021 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.subjectRefuse Sorting
dc.subjectImage Recognition
dc.subjectProcess Monitoring
dc.subjectOptimisation
dc.subjectWorker Support
dc.titleKI-Waste - Combining Image Recognition and Time Series Analysis in Refuse Sortingen
dc.typeText/Workshop Paper
gi.citation.publisherPlaceBonn
gi.conference.date5.-8. September 2021
gi.conference.locationIngolstadt
gi.conference.sessiontitleMCI-WS04: Smart Collaboration – Employee-Centric Information Systems in Product Creation
gi.document.qualitydigidoc

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