An Intelligent Scanning Vehicle for Waste Collection Monitoring

Georg Waltner*, Malte Jaschik, Alfred Rinnhofer, Horst Possegger, Horst Bischof

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

While many industries have adopted digital solutions to improve ecological footprints and optimize services, new technologies have not yet found broad acceptance in waste management. In addition, past efforts to motivate households to improve waste separation have shown limited success. To reduce greenhouse gas emissions as part of a greater plan for fighting climate change, institutions like the European Union (EU) undertake strong efforts. In this context, developing intelligent digital technologies for waste management helps to increase the recycling rate and as a consequence reduces greenhouse gas emissions. Within this work, we propose an innovative computer vision system that is able to assess the residential waste in real-time and deliver individual feedback to the households and waste management companies with the aim of increasing recycling rates and thus reducing emissions. It consists of two core components: A compact scanning hardware designed specifically for rugged environments like the innards of a garbage truck and an intelligent software that applies a convolutional neural network (CNN) to automatically identify the composition of the waste which was dumped into the truck and subsequently delivers the results to a web portal for further analysis and communication. We show that our system can impact household separation behavior and result in higher recycling rates leading to noticeable reduction of CO2 emissions in the long term.
Original languageEnglish
Title of host publicationImage Analysis and Processing – ICIAP 2022 - 21st International Conference, 2022, Proceedings
Subtitle of host publication21st International Conference, Lecce, Italy, May 23–27, 2022, Proceedings, Part I
EditorsStan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
Place of PublicationCham
Pages38-50
Number of pages13
ISBN (Electronic)978-3-031-06427-2
DOIs
Publication statusPublished - May 2022
Event16th International Conference on Image Analysis and Processing: ICIAP 2022 - Paris, France
Duration: 27 Oct 202228 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13231 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Image Analysis and Processing
Abbreviated titleICIAP 2022
Country/TerritoryFrance
CityParis
Period27/10/2228/10/22

Keywords

  • Circular economy
  • Cloud computing
  • Computer vision
  • Convolutional neural networks
  • Deep learning

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Theoretical Computer Science
  • Computer Science(all)

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