%A Dang Nhac Lu
%A Thu Trang Nguyen
%A Thi Thu Trang Ngo
%A Thi Hau Nguyen
%A Ha Nam Nguyen
%J Advances in Information and Communication Technology
%T Mobile Online Activity Recognition System Based on Smartphone Sensors
%X 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.
%P 357-366
%B Advances in Information and Communication Technology
%V 538
%D 2016
%R doi:10.1007/978-3-319-49073-1_39
%L SisLab1897