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A Machine Learning Driven IoT Solution for Noise Classification in Smart Cities
Linnaeus University, Faculty of Technology, Department of Physics and Electrical Engineering.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (Parallel Computing)ORCID iD: 0000-0002-4146-9062
RISE Interactive, Sweden.ORCID iD: 0000-0003-0512-6350
2018 (English)In: Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic, Euromicro , 2018, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

We present a machine learning based method for noise classification using a low-power and inexpensive IoT unit. We use Mel-frequency cepstral coefficients for audio feature extraction and supervised classification algorithms (that is, support vector machine and k-nearest neighbors) for noise classification. We evaluate our approach experimentally with a dataset of about 3000 sound samples grouped in eight sound classes (such as, car horn, jackhammer, or street music). We explore the parameter space of support vector machine and k-nearest neighbors algorithms to estimate the optimal parameter values for classification of sound samples in the dataset under study. We achieve a noise classification accuracy in the range 85% -- 100%. Training and testing of our k-nearest neighbors (k = 1) implementation on Raspberry Pi Zero W is less than a second for a dataset with features of more than 3000 sound samples.

Place, publisher, year, edition, pages
Euromicro , 2018. p. 1-6
Keywords [en]
urban noise, smart cities, support vector machine (SVM), k-nearest neighbors (KNN), mel-frequency cepstral coefficients (MFCC), internet of things (IoT)
National Category
Computer Systems
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-81672OAI: oai:DiVA.org:lnu-81672DiVA, id: diva2:1302435
Conference
Machine Learning Driven Technologies and Architectures for Intelligent Internet of Things (ML-IoT), August 28, 2018, Prague, Czech Republic
Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-05-20Bibliographically approved

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Pllana, SabriKurti, Arianit

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Alsouda, YasserPllana, SabriKurti, Arianit
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • 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