Kim, YoungwooEyobu, Odongo StevenSeog Han, Dong2023-02-032023-02-032018Kim, 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.Kim, 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.https://nru.uncst.go.ug/handle/123456789/7513Position 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.enANN-based Stride DetectionSmartphonesPedestrianDeadOther