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Related Experiment Video

Updated: May 18, 2026

Determining Viral Disinfection Efficacy of Hot Water Laundering

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Published on: June 21, 2022

Household Laundry Appliance Resource Consumption and Operation Dataset.

Žygimantas Jasiūnas¹, João Braz Ferreira², Tiago Julião³

¹LASIGE, Faculty of Sciences, University of Lisbon, Lisbon, Portugal. zjasiunas@ciencias.ulisboa.pt.

Scientific Data

|May 16, 2026

Summary

The new LARCO dataset captures real-world washing machine and dryer usage, revealing how user behaviour impacts appliance energy and water consumption beyond official energy labels.

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Area of Science:

Sustainable energy consumption
Household appliance efficiency
Behavioural science in energy use

Background:

Household appliances like washing machines and dryers are major residential energy consumers.
Energy labels don't fully capture real-world energy and water usage due to user behaviour and operating conditions.
Existing datasets often overlook user behaviour in appliance operation.

Purpose of the Study:

To introduce the Laundry Appliance Resource Consumption and Operation (LARCO) dataset.
To provide a comprehensive, open-access resource for studying appliance efficiency and user behaviour.
To bridge the gap between labelled and actual appliance performance for sustainable energy use.

Main Methods:

Collected multivariate time-series data (1 Hz+) from washing machines and dryers under laboratory and household conditions.
Recorded energy, water, temperature, and humidity, alongside metadata for various operational parameters.
Included data on load sizes, programme settings, and ambient conditions for comprehensive analysis.

Main Results:

The LARCO dataset offers detailed operational and environmental data, capturing real-world usage variability.
It provides ground-truth laboratory measurements and diverse household usage patterns.
Enables in-depth analysis of factors influencing appliance resource consumption.

Conclusions:

The LARCO dataset is crucial for understanding and modelling user behaviour's impact on appliance efficiency.
It facilitates the development of personalized energy feedback and more effective energy-saving strategies.
Promotes more sustainable residential energy consumption by addressing the performance gap.