Appliances Energy Prediction Smart Home Dataset
Catalog Summary
"Real smart-home energy consumption data (10-minute resolution) with indoor room sensors and outdoor weather measurements, designed to model appliance energy use in a low-energy house.[web:55][web:61][web:66]"
Catalog Notes
Overview
The Appliances Energy Prediction dataset contains experimental data collected in a real low-energy house to build regression models for household appliance energy consumption.[web:55][web:61][web:66]
Data Collection
- 19,735 observations sampled every 10 minutes over approximately 4.5 months.[web:55][web:61]
- Indoor environmental conditions were monitored in 9 rooms using a ZigBee wireless sensor network.[web:55]
- Outdoor weather and climate variables were obtained from the Chievres airport weather station.[web:55]
Features
- Target variable: Total energy use of appliances (in Wh or kWh, depending on pre-processing) for each 10-minute interval.[web:55][web:61]
- Indoor variables: temperature and humidity measurements for 9 rooms (kitchen, living room, bathrooms, office, etc.).[web:55]
- Outdoor variables: temperature, pressure, humidity, wind speed, visibility and dew point from the nearby weather station.[web:55]
- Time-related attributes (date, time) enabling temporal feature engineering and seasonality analysis.[web:55][web:61]
Typical Use Cases
- Smart home energy demand forecasting and load profiling.[web:55][web:58]
- Learning control policies for HVAC optimization and comfort–energy tradeoffs.[web:55][web:63]
- Benchmarking regression and time-series ML models on real IoT energy data.[web:55][web:61]
License
The UCI page specifies that this dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which allows sharing and adaptation with proper credit.[web:66]
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on UCI Machine Learning Repository.
Preview on UCI Machine Learning RepositoryCite This Dataset
UCI Machine Learning Repository (2017). Appliances Energy Prediction Data Set. [Dataset]. UCI Machine Learning Repository. https://archive.ics.uci.edu/dataset/374/appliances+energy+prediction
Source metadata: UCI Machine Learning Repository (2017)
Indexed by IoTDataset.com on Jan 26, 2026
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