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Mobile Online Activity Recognition System Based on Smartphone Sensors

Dang Nhac Lu and Thu Trang Nguyen and Thi Thu Trang Ngo and Thi Hau Nguyen and Ha Nam Nguyen (2016) Mobile Online Activity Recognition System Based on Smartphone Sensors. Advances in Information and Communication Technology, 538 . pp. 357-366. ISSN 2194-5357

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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.

Item Type:Article
Subjects:Information Technology (IT)
ISI-indexed journals
Divisions:Faculty of Information Technology (FIT)
ID Code:1897
Deposited By: Nguy�n Th
Deposited On:21 Nov 2016 06:35
Last Modified:21 Nov 2016 06:35

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