Development of an Intelligent Remote Sensing Technique as a Tool for Smart Infrastructure Asses Management

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
LanguageEnglish
Title of host publicationProceedings of International Conference on Smart Cities (ICSC-2019)
Pages1-7
Number of pages7
Publication statusAccepted/In press - 19 Apr 2019
EventInternational Conference on Smart Cities (ICSC-2019) - South Korea, Seoul, Korea, Republic of
Duration: 17 Jul 201919 Jul 2019
http://icsc2019.org/conference-overview/

Conference

ConferenceInternational Conference on Smart Cities (ICSC-2019)
CountryKorea, Republic of
CitySeoul
Period17/07/1919/07/19
Internet address

Fingerprint

Roadsides
Remote sensing
Polyethylene terephthalates
Plastic containers
Level control
Learning systems
Cleaning
Image processing
Plastics
Economics
Sensors
Costs

Keywords

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

Cite this

Magee, B., Hamill, M., & Millar, P. (Accepted/In press). Development of an Intelligent Remote Sensing Technique as a Tool for Smart Infrastructure Asses Management. In Proceedings of International Conference on Smart Cities (ICSC-2019) (pp. 1-7)
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title = "Development of an Intelligent Remote Sensing Technique as a Tool for Smart Infrastructure Asses Management",
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.",
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Magee, B, Hamill, M & Millar, P 2019, Development of an Intelligent Remote Sensing Technique as a Tool for Smart Infrastructure Asses Management. in Proceedings of International Conference on Smart Cities (ICSC-2019). pp. 1-7, International Conference on Smart Cities (ICSC-2019), Seoul, Korea, Republic of, 17/07/19.

Development of an Intelligent Remote Sensing Technique as a Tool for Smart Infrastructure Asses Management. / Magee, Bryan; Hamill, Mark; Millar, Phillip.

Proceedings of International Conference on Smart Cities (ICSC-2019). 2019. p. 1-7.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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