Reliable context capturing for smart offices using a sensor network. (19th May 2011)

• Record Type: Journal Article
• Authors: Aida, Hiroto; Nakazawa, Jin; Tokuda, Hideyuki
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 7:Number 3(2011)
• Page Start: 174
• Page End: 183
• Publication Date: 2011-05-19
• Subjects: wireless sensor networks -- WSNs -- Bayesian networks -- air conditioning -- smart offices -- context classification -- digital offices -- wireless networks -- Bayesian inference -- posterior probability tables -- disruption tolerance -- air conditioner control -- comfort level -- air conditioners; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

In order to realise smart offices, which provides users with comfort via various digital services, we need to acquire context information about the target space. Contexts can be obtained from raw sensor data using context classification methods, such as Bayesian network. However, packet losses and disrupted communications in wireless sensor networks disables the context classification methods to collect all the necessary data, hence reduce quality of contexts. In this paper, we propose Reliable Hybrid Bayesian Inference Mechanism (RHBIM) that features in-network disruption-tolerant Bayesian inference with server-side calculation of Posterior Probability Tables. In this paper, we show the design and implementation of the mechanism with a range of disruption-tolerance schemes, and apply the mechanism to an application that controls air conditioners based on the ('comfort level') context. We also show the effectiveness of the mechanism comparing the different disruption-tolerance schemes.