Detecting Swimming Pools in 15-Minute Load Data

摘要

The ability to detect appliances in load data highly depends on the resolution of the data. While a lot of related work exists on detecting appliances in second or sub-second granularity load data, in this paper, we detect swimming pools through their filter pumps in load data with the 15-minute granularity prescribed by the European Union for smart meters. We model the filter pump based on exemplary measurements and describe a prototypical algorithm to extract the filter pump's consumption from the aggregated mains signal of a real-world household. We evaluate pool detection performance with different classifiers on a data set with 843 households, where the information on the existence of a swimming pool is available. We achieve 94.8% detection accuracy with a precision of 68.5% with an off-the-shelf classifier. Decreasing the temporal resolution in several steps to 8 hours negatively affects the recall while the precision stays at the same level. We find that these results raise privacy concerns even at the minimum temporal resolution of smart meter data that is legally required in the European Union.