relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1897/
title: Mobile Online Activity Recognition System Based on Smartphone Sensors
creator: Lu, Dang Nhac
creator: Nguyen, Thu Trang
creator: Ngo, Thi Thu Trang
creator: Nguyen, Thi Hau
creator: Nguyen, Ha Nam
subject: Information Technology (IT)
subject: ISI-indexed journals
description: In this paper, we propose an efficient and flexible framework for activity recognition based on smartphone sensors. We develop a mobile application that integrates data collection, training and recognition, feedback monitoring. This system allows user smartphones are randomly placed in any position and at any direction. In the proposed framework, a set of power based and frequency-based features is extracted from sensor data. Then, we deploy Random Forest, Naïve Bayes, K-Nearest Neighbor (KNN), Support Vector Ma-chine (SVM) classification algorithms for recognizing a set of user activities. Our framework dynamically takes into account real-time user feedbacks to increase the prediction accuracy. Our framework will be able to apply for intelligent mo-bile applications. A number of experiments were carried out to show the high ac-curacy of the proposed framework for detecting user activities when walking or driving a motorbike.
date: 2016
type: Article
type: PeerReviewed
identifier:   Lu, Dang Nhac and Nguyen, Thu Trang and Ngo, Thi Thu Trang and Nguyen, Thi Hau and Nguyen, Ha Nam  (2016) Mobile Online Activity Recognition System Based on Smartphone Sensors.  Advances in Information and Communication Technology, 538 .   pp. 357-366.  ISSN 2194-5357     
relation: http://doi.org/10.1007/978-3-319-49073-1_39
relation: doi:10.1007/978-3-319-49073-1_39