eprintid: 1897
rev_number: 8
eprint_status: archive
userid: 283
dir: disk0/00/00/18/97
datestamp: 2016-11-21 06:35:24
lastmod: 2016-11-21 06:35:24
status_changed: 2016-11-21 06:35:24
type: article
metadata_visibility: show
creators_name: Lu, Dang Nhac
creators_name: Nguyen, Thu Trang
creators_name: Ngo, Thi Thu Trang
creators_name: Nguyen, Thi Hau
creators_name: Nguyen, Ha Nam
creators_id: nguyenhau@vnu.edu.vn
creators_id: namnh@vnu.edu.vn
title: Mobile Online Activity Recognition System Based on Smartphone Sensors
ispublished: pub
subjects: IT
subjects: isi
divisions: fac_fit
abstract: 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
date_type: published
official_url: http://doi.org/10.1007/978-3-319-49073-1_39
id_number: doi:10.1007/978-3-319-49073-1_39
full_text_status: none
publication: Advances in Information and Communication Technology
volume: 538
pagerange: 357-366
refereed: TRUE
issn: 2194-5357
book_title: Advances in Information and Communication Technology
citation:   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