ANN-based Stride Detection Us ing Smartphones for Pedestrian Dead Reckoning

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dc.contributor.authorKim, Youngwoo
dc.contributor.authorEyobu, Odongo Steven
dc.contributor.authorSeog Han, Dong
dc.date.accessioned2023-02-03T15:55:03Z
dc.date.available2023-02-03T15:55:03Z
dc.date.issued2018
dc.description.abstractPosition awareness is a very important issue for internet of thing (IoT) applications using smartphones. Pedestrian dead reckoning (PDR) is one of the methods used to estimate a user’s indoor position. The accuracy of a stride detection is very important to guarantee the estimation accuracy of the user location. This paper proposes an algorithm to detect the stride using acceleration spectrogram feature by utilizing the accelerometer in a smartphone. An artificial neural network (ANN) technology is applied to detect the stride. The proposed algorithm has an accuracy of 97.7% for stride detection.en_US
dc.identifier.citationKim, Y., Eyobu, O. S., & Han, D. S. (2018, January). ANN-based stride detection using smartphones for Pedestrian dead reckoning. In 2018 IEEE International Conference on Consumer Electronics (ICCE) (pp. 1-2). IEEE.en_US
dc.identifier.uriKim, Y., Eyobu, O. S., & Han, D. S. (2018, January). ANN-based stride detection using smartphones for Pedestrian dead reckoning. In 2018 IEEE International Conference on Consumer Electronics (ICCE) (pp. 1-2). IEEE.
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/7513
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectANN-based Stride Detectionen_US
dc.subjectSmartphonesen_US
dc.subjectPedestrianen_US
dc.subjectDeaden_US
dc.titleANN-based Stride Detection Us ing Smartphones for Pedestrian Dead Reckoningen_US
dc.typeOtheren_US
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