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Effective machine learning techniques for detecting inflow and infiltration water in wastewater channels
Kristianstad University, Faculty of Natural Sciences.
Kristianstad University, Faculty of Natural Sciences.
2021 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In this degree thesis, the research team analyses different ways of monitoring water flow in wastewater channels finds an effective way of processing data using machine learning on collected data from a specific area and sets up a system for finding correlations between rain levels, water usages and wastewater flow to detect infiltrations and inflow water in wastewater channels. The study concludes that a sensor network is most suited for monitoring wastewater channels and that machine learning could be used to detect infiltration and inflow water using different types of data. 

Place, publisher, year, edition, pages
2021. , p. 52
Keywords [en]
Inflow, infiltration, machine learning, sensor network, wastewater channels
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hkr:diva-22505OAI: oai:DiVA.org:hkr-22505DiVA, id: diva2:1589754
External cooperation
Jonas Johansson
Educational program
Bachelor programme in Computer Software Development
Presentation
2021-05-31, Online, Kristianstad, 13:00 (English)
Supervisors
Examiners
Available from: 2021-09-01 Created: 2021-08-31 Last updated: 2021-09-01Bibliographically approved

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fulltext(1197 kB)1017 downloads
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf