Home // MOBILITY 2014, The Fourth International Conference on Mobile Services, Resources, and Users // View article

A Non-GPS Low-power Context-aware System using Modular Bayesian Networks' submitted to MOBILITY 2014

Authors:
Kyon-Mo Yang
Sung-Bae Cho

Keywords: Low-power system, context-awareness, modular Bayesian network, Markov boundary

Abstract:
The proliferation of smartphones has lead to the development of a large variety of applications and the inverstigation on the use of various sensors through context-awareness, in order to provide better services. However, smartphone battery capacity is extremely limited so that the applications cannot be effectively used. In this paper, we propose a low-power context-aware system using modular Bayesian networks. Bayesian networks are known to respond flexibly to uncertain situations. However, probabilistic models such as Bayesian networks have high time complexity, resulting in high power consumption. To reduce the time complexity we modularize the network based on the Markov boundary, and eliminate the use of GPS because it consumes a lot of power. We compare the accuracy of the system using a combination of sensors and confirm the decrease in the time complexity. Experiments with the real data collected show that the proposed Bayesian networks yield an accuracy of 92.47%.

Pages: 19 to 24

Copyright: Copyright (c) IARIA, 2014

Publication date: July 20, 2014

Published in: conference

ISSN: 2308-3468

ISBN: 978-1-61208-366-7

Location: Paris, France

Dates: from July 20, 2014 to July 24, 2014