<p>Household appliances, particularly washing machines and tumble dryers, account for a significant share of residential energy consumption. While energy labelling aims to encourage the adoption of more efficient appliances, actual energy and water usage are highly influenced by user behaviour and operating conditions. The user behaviour is often overlooked in existing datasets. To address this gap, the household Laundry Appliance Resource Consumption and Operation dataset (LARCO) is presented: a comprehensive, open-access dataset capturing detailed operational and environmental data from washing machines and dryers under laboratory and household conditions. The dataset includes multivariate time-series recordings at 1 Hz (and higher for vibrations and audio), covering a range of load sizes, programme settings, and ambient conditions. Laboratory data provide ground-truth measurements under controlled conditions, while household data capture real-world usage variability. Each sample includes energy, water, temperature, and humidity measurements, associated with the corresponding metadata. LARCO enables studies on appliance efficiency, user behaviour modelling, and personalised energy feedback. It supports the development of more effective strategies to bridge the gap between labelled and actual appliance performance, promoting more sustainable energy use.</p>

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Household Laundry Appliance Resource Consumption and Operation Dataset

  • Žygimantas Jasiūnas,
  • João Braz Ferreira,
  • Tiago Julião,
  • José Cecílio,
  • Guilherme Carrilho da Graça,
  • Pedro M. Ferreira

摘要

Household appliances, particularly washing machines and tumble dryers, account for a significant share of residential energy consumption. While energy labelling aims to encourage the adoption of more efficient appliances, actual energy and water usage are highly influenced by user behaviour and operating conditions. The user behaviour is often overlooked in existing datasets. To address this gap, the household Laundry Appliance Resource Consumption and Operation dataset (LARCO) is presented: a comprehensive, open-access dataset capturing detailed operational and environmental data from washing machines and dryers under laboratory and household conditions. The dataset includes multivariate time-series recordings at 1 Hz (and higher for vibrations and audio), covering a range of load sizes, programme settings, and ambient conditions. Laboratory data provide ground-truth measurements under controlled conditions, while household data capture real-world usage variability. Each sample includes energy, water, temperature, and humidity measurements, associated with the corresponding metadata. LARCO enables studies on appliance efficiency, user behaviour modelling, and personalised energy feedback. It supports the development of more effective strategies to bridge the gap between labelled and actual appliance performance, promoting more sustainable energy use.