Improving home automation by discovering regularly occurring device usage patterns
- 30 March 2004
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The data stream captured by recording inhabitant-deviceinteractions in an environment can be mined todiscover significant patterns, which an intelligent agentcould use to automate device interactions. However, thisknowledge discovery problem is complicated by severalchallenges, such as excessive noise in the data, data thatdoes not naturally exist as transactions, a need tooperate in real time, and a domain where frequency maynot be the best discriminator. In this paper, we propose anovel data mining technique that addresses thesechallenges and discovers regularly-occurringinteractions with a smart home. We also discuss a casestudy that shows the data mining technique can improvethe accuracy of two prediction algorithms, thusdemonstrating multiple uses for a home automationsystem. Finally, we present an analysis of the algorithmand results obtained using inhabitant interactions.Keywords
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