Can smartphones be used to detect an earthquake? Using a machine learning approach to identify an earthquake event

Alham Fikri Aji, I. Putu Edy Suardiyana Putra, Petrus Mursanto, Setiadi Yazid

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

4 Citations (Scopus)

Abstract

The possibility of using smart phone accelerometer to detect earthquake is investigated in this research. Experiments are designed to learn the pattern of an earthquake signal recorded from smart phone's accelerometer. The signal is processed using N-gram modeling as feature extractor for machine learning. For the classifier, this study use Naïve Bayes, Multi-Layer Perceptron (MLP), and Random Forest. Our result shows that the best classification accuracy is achieved by Random Forest method. Its accuracy reached 93.15%. It can be concluded that smart phones can be used as an earthquake detector.

Original languageEnglish
Title of host publicationSysCon 2014
Subtitle of host publication8th Annual IEEE International Systems Conference : proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages72-77
Number of pages6
ISBN (Print)9781479920877
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event8th Annual IEEE International Systems Conference, SysCon 2014 - Ottawa, ON, Canada
Duration: 31 Mar 20143 Apr 2014

Other

Other8th Annual IEEE International Systems Conference, SysCon 2014
CountryCanada
CityOttawa, ON
Period31/03/143/04/14

Keywords

  • signal processing
  • n-gram
  • machine learning
  • earthquake

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  • Cite this

    Fikri Aji, A., Putra, I. P. E. S., Mursanto, P., & Yazid, S. (2014). Can smartphones be used to detect an earthquake? Using a machine learning approach to identify an earthquake event. In SysCon 2014: 8th Annual IEEE International Systems Conference : proceedings (pp. 72-77). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SysCon.2014.6819238