Subject-independent human activity recognition using Smartphone accelerometer with cloud support Online publication date: Thu, 26-Nov-2015
by Muhammad Arshad Awan; Zheng Guangbin; Hie-Cheol Kim; Shin-Dug Kim
International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC), Vol. 20, No. 3, 2015
Abstract: Human activity recognition is an important task in providing contextual user information. In this study, we present a methodology to achieve human activity recognition using a Smartphone accelerometer independent of a subject compared with other user-dependent solutions. The proposed system is composed of four components; a data collector, a data storage cloud, a workstation module and an activity recogniser. The data collector extracts a unique set of defined features from raw data and sends them to the data storage cloud. The workstation module receives the training data from the cloud and generates classification models. The activity recogniser determines the user's current activity based on up-to-date available classifier from the cloud. A prototype is implemented on an android platform to recognise a set of basic daily living activities by placing the Smartphone in different positions to the user and evaluated for offline and online testing to show the scalability and effectiveness.
Online publication date: Thu, 26-Nov-2015
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org