The Impact of Temporal Granularity on Socio-Demographic Inference from Household Load Profiles
Smart meter data can reveal sensitive socio-demographic characteristics of households, raising privacy concerns. While this risk has been demonstrated at fixed granularities, the role of temporal resolution in shaping inference performance remains insufficiently explored. This paper addresses this gap by analyzing how load profiles with granularities from 15 minutes to 7 days affect the predictability of eight socio-demographic attributes in a dataset of 1,589 households over one year. We introduce an evaluation framework where classifiers are trained on year-round data but tested on arbitrary weeks, forcing generalization across seasonal and weekly variations. Our results show three main...
| Authors | Dejan Radovanovic, Maximilian Schirl, Andreas Unterweger et al. |
|---|---|
| Primary category | cs.LG |
| Published | 2 June 2026 |
| Last updated at source | 2 June 2026 |
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