LARCO - Household Laundry Appliance Resource Consumption and Operation Dataset

LARCO: Household Laundry Appliance Resource Consumption and Operation Dataset

Household laundry appliances such as washing machines and tumble dryers represent a significant share of residential energy and water consumption. While efficiency labels provide standardised performance indicators, the actual use of resources depends heavily on user behaviour, laundry load, programme selection, and ambient conditions. These aspects are often underrepresented in existing datasets.

The LARCO dataset addresses this gap by providing a comprehensive, open-access collection of multivariate time-series measurements of washing machines and dryers, recorded under both laboratory-controlled conditions and real-world household usage.

The dataset was created following strategic and systematic data collection protocols designed to capture the performance of household laundry appliances under both controlled and real-world conditions. By combining laboratory experiments with carefully varied parameters (ambient temperature, load sizes, and cycle programmes) and long-term household monitoring, the dataset provides a structured and comprehensive view of appliance operation.

Key recorded variables include:

Energy: voltage, current, power, power factor, frequency

Water system: inlet/outlet flow, volumes, temperatures, and pressure

Appliance temperatures: drum, door, and lint trap sensors

Indoor environment: ambient temperature and humidity

Additional modalities: three-axis vibration (200 Hz), audio recordings (11 kHz, lab only, privacy-safe), laundry weights (pre/post cycle), dryer tank water volumes, and cycle metadata.

Supplementary weather data: Temperature, humidity and atmospheric pressure in acquisition location based on data acquisition timestamps.

Dataset structure

The dataset is organised into three main modalities. Each observation may include up to three parallel data streams: (i) general data capturing energy, environmental, and operational measurements, (ii) vibration data from accelerometer sensors, and (iii) audio data from laboratory recordings. These are distributed as separate ZIP archives.

general.zip: Where the main sensor data of 1Hz is stored from three environments:

Laboratory: Controlled experiments at 16 °C, 25 °C, and 31 °C with systematic variation of load sizes (0 kg up to maximum capacity –1 kg) and washing/drying programmes.

Household: Real-world monitoring of 15 appliances across 10 homes (2004–2020), capturing natural variability in use.

Exploratory: Early recordings for testing and validation.

vibrations.zip: where all the accelerometer sensor files are stored, it includes two environments:

Laboratory

Household

audio.zip: where all the audio files are stored from the laboratory environment. 

! The original WAV files were compressed using FLAC. To convert them back to WAV run the following command: 

find audio -type f -name "*.flac" -exec flac -d {} \;

Each cycle includes 1 Hz general data files, optional 200 Hz accelerometer files, and 11 kHz audio files (for some laboratory appliances). Metadata files provide appliance details, sensor specifications, units, sampling frequencies, and environment information. Each zip file contains an aggregated CSV summary, and additional metadata about each experiment is also included for quick access: general_data.csv, general_data_acc.csv andgeneral_data_audio.csv. Each zip file contains metadata.xlsx file with the detailed information about sensor types and models, their descriptions and acquisition frequencies.

Applications

The dataset supports research in:

Appliance efficiency assessment and benchmarking

User behaviour analysis and modelling

Intrusive and non-intrusive load monitoring (ILM/NILM)

Personalised energy feedback and eco-feedback systems

Demand-side management and sustainable energy strategies

Availability

Data are provided as raw sensor time-series without post-processing, ensuring maximum flexibility for downstream use. Aggregated and metadata files facilitate navigation, filtering, and integration into analytical workflows.

If you use this dataset, please cite the accompanying data descriptor:

Jasiūnas, Ž., Braz Ferreira, J., Julião, T., Cecílio, J., Carrilho da Graça, G., & Ferreira, P. M. (2026). Household Laundry Appliance Resource Consumption and Operation Dataset. Scientific Data. https://doi.org/10.1038/s41597-026-07361-6Licensing information:

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This deposit contains files under different licenses. Please refer to the
mapping below to ensure you comply with the terms for each specific file.

1. DATASET
- vibrations.zip
- audio.zip
- general.zip
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
URL: https://creativecommons.org/licenses/by/4.0/
Summary: You are free to share (copy and redistribute) and adapt (remix, transform,or build upon) the material in any medium or format for any purpose, evencommercially. You must give appropriate credit, provide a link to the license, andindicate if changes were made. You may do so in any reasonable manner, but not inany way that suggests the licensor endorses you or your use. You may not apply legalterms or technological measures that legally restrict others from doing anything thelicense permits.

2. OTHER ASSETS
File: weather_data.csv
Source: OpenWeather (https://openweathermap.org/)
License: Open Data Commons Open Database License (ODbL) v1.0
URL: https://opendatacommons.org/licenses/odbl/1-0/
Summary: You are free to share, create, and adapt the database, provided
you attribute the source and keep the open license on any derivative work.

2. SOFTWARE / CODE
Files: /scripts folder (and all contents therein)
License: MIT License
Summary: Permission is granted, free of charge, to any person obtaining
a copy of this software and associated documentation files.

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DISCLAIMER: The licenses listed above apply to the specific files indicated.