Real-time event detection for energy data streams

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Abstract

Appliance specific energy monitoring is perceived as a prerequisite for reducing energy usage in households. A number of approaches exist, however, Non-Intrusive appliance Load Monitoring is considered to be the most promising and scalable method. This method can also facilitate Ambient Intelligent applications with the hope activity recognition of the resident is of paramount importance. In this paper, we propose an event detection algorithm to support non-intrusive energy monitoring. A performance evaluation of this algorithm has been carried out on a reference dataset.

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Kazmi, A. H., O’Grady, M. J., & O’Hare, G. M. P. (2014). Real-time event detection for energy data streams. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8850, 221–225. https://doi.org/10.1007/978-3-319-14112-1_18

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