Application of remote sensing for automated litter detection and management

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Abstract

The Clean Europe Network (CEN) estimates that cleaning litter in the EU accounts for€10-13 billion of public expenditure every year.The annual budget for managing roadside litter alone,is approximately €1 billion.While local authorities in Northern Ireland and elsewhere have legal requirements to monitor and control litter levels, requirements for compliance are unclear and frequently ignored. Against this background, the overall objective of this research is to develop an integrated management system allowing remote discrimination and quantification of roadside litter. As such, the intention is that local authorities can more effectively meet their statutory requirements with regards to litter management. The research aligns with objectives outlined by the UK Government and CEN in terms of improving litter-related data levels. As plastic containers of type RIC1, Polyethylene terephthalate (PETE),represent one of the most common components of roadside litter, its identification in the natural environment via remote sensing is a key objective. By combining published US Hyperspectral library data and experimental field study results, the initial findings of this research indicate that it is possible to discriminate PETE plastic samples in a grass background using a low-cost multispectral sensor primarily designed for agricultural use. While at an initial phase, the research presented has the potential to have a significant impact on the economic, environmental and statutory implications of roadside litter management.Future work will employ image processing and machine learning techniques to deliver a methodology for automatic identification and quantification of multiple roadside litter types.
Original languageEnglish
Title of host publicationAdvances in Computer Vision - Proceedings of the 2019 Computer Vision Conference CVC
Subtitle of host publicationProceedings of the 2019 Computer Vision Conference (CVC), Volume 2
EditorsSupriya Kapoor, Kohei Arai
PublisherSpringer International Publishing
Pages157-168
Number of pages12
Volume944
ISBN (Electronic)978-3-030-17798-0
ISBN (Print)978-3-030-17797-3
DOIs
Publication statusE-pub ahead of print - 24 Apr 2019
EventComputer Vision Conference 2019 - Vdara Hotel & Spa , Las Vegas, United States
Duration: 25 Apr 201926 Apr 2019
https://saiconference.com/CVC

Publication series

NameAdvances in Intelligent Systems and Computing

Conference

ConferenceComputer Vision Conference 2019
Abbreviated titleCVC 2019
CountryUnited States
CityLas Vegas
Period25/04/1926/04/19
Internet address

Keywords

  • Image analysis
  • Multispectral
  • Litter
  • Remote sensing
  • Hyperspectral signatures

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