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ICDM
2003
IEEE

Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns

10 years 1 months ago
Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns
The data stream captured by recording inhabitantdevice interactions in an environment can be mined to discover significant patterns, which an intelligent agent could use to automate device interactions. However, this knowledge discovery problem is complicated by several challenges, such as excessive noise in the data, data that does not naturally exist as transactions, a need to operate in real time, and a domain where frequency may not be the best discriminator. In this paper, we propose a novel data mining technique that addresses these challenges and discovers regularly-occurring interactions with a smart home. We also discuss a case study that shows the data mining technique can improve the accuracy of two prediction algorithms, thus demonstrating multiple uses for a home automation system. Finally, we present an analysis of the algorithm and results obtained using inhabitant interactions.
Edwin O. Heierman III, Diane J. Cook
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICDM
Authors Edwin O. Heierman III, Diane J. Cook
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