Real-time analytics to determine the quality of input in waste pre-treatment plants

Thomas Weißenbach, Roland Pomberger, Renato Sarc

Research output: Contribution to conferencePaperpeer-review


In the framework of a larger project (ReWaste4.0), research work is carried out to char-acterise input into waste pre-treatment plants by means of real-time analysis. Commer-cial waste was selected as input material for the experiments. A number of samples were pre-processed (shredding, sieving) and sorted into a number of fractions. The main experiments will be carried out with individual waste objects, which are taken from nine sorting fractions. Regarding the real-time analysis, two approaches will be used, i.e. sensor-bases analysis (NIR-sensor/RGB-camera) and a deep learning ap-proach (image classification system). The produced data are related to data, which are generated by manual measuring (object size, weight) and laboratory analysis (heating value, water and chlorine content). By using regression analysis, the data of the real-time analysis are related to the data of standard laboratory analysis.
Translated title of the contributionEchtzeitanalytik zur Bestimmung der Qualität des Inputs in Abfallvorbehandlungsanlagen
Original languageEnglish
Pages130 - 138
Number of pages9
Publication statusPublished - 15 May 2019
EventWaste to resources 2019 - Hotel Wienecke 11, Hannover, Germany
Duration: 14 May 201916 May 2019


ConferenceWaste to resources 2019

Cite this