Skip to main content
Kaggle

A three-year dataset supporting research on building energy management and occupancy analytics

Smart Home & Buildings Smart Home
672 views
1 min read
License
Catalog metadata: This page is a discovery record, not publisher documentation. Verify the description, schema, provenance, version, licence, and citation at the linked source before use.

Catalog Summary

"A high-resolution, three-year dataset from a real office building, integrating whole-building/end-use energy consumption, HVAC system data, environmental parameters, and ground-truth occupant counts. Essential for research in smart building energy prediction, optimization, and occupancy analytics."

Catalog Notes

This comprehensive dataset was curated to support advanced research in smart building energy management. It captures the complex interplay between energy use, building systems, and human occupancy in a medium-sized office building constructed in 2015.

Key Features & Applications:

  • Data Richness: Over 300 sensors collected data on electricity consumption (whole-building and end-use), HVAC operating conditions, indoor/outdoor temperatures, and precise occupant counts via cameras and WiFi proxies.
  • Temporal Scope: Includes two years of pre-pandemic operation (2018-2019) and one year impacted by COVID-19 (2020), offering unique insights into pandemic effects on building energy patterns.
  • Research Applications: Designed for building energy benchmarking, load shape analysis, energy and occupancy prediction, HVAC model predictive control (MPC) validation, and fault detection diagnostics.
  • Data Quality: Underwent a rigorous three-step curation process: data cleaning, metadata modeling using the Brick schema, and representation via a semantic JSON schema for high quality and usability.

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.

Preview on Kaggle

Cite This Dataset

The dataset creators ask users of this dataset to cite the accompanying paper. Use one of the verified formats below.

Luo, N., Wang, Z., Blum, D., Weyandt, C., Granderson, J., Spanos, C. J., & Hong, T. (2022). A three-year dataset supporting research on building energy management and occupancy analytics. Scientific Data, 9(1), 156. https://doi.org/10.1038/s41597-022-01257-x

Source metadata: Nature Portfolio (2022) · DOI: 10.1038/s41597-022-01257-x

Indexed by IoTDataset.com on Feb 10, 2026

Review the Source Record

Confirm the licence, version, access conditions, file format, and provenance at the source before use.

Open Source Page

Related Topics & Keywords

Browse all Smart Home & Buildings datasets

Share This Research

More in Smart Home & Buildings

View All
Smart Home IoTSyn Generated

Synthetic Smart Home IoT Sensor Dataset — 1K Rows

Free CC0 synthetic dataset: 1,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Reproducible from its seed.

Apr 02, 2026
Smart Home Kaggle

Hourly Energy Consumption Data for a Commercial Building

A real-world, hourly dataset of electricity, heating, and cooling consumption for a commercial building, ideal for benchmarking and building energy model calibration.

Feb 10, 2026
Smart Home Kaggle

Smart Home IoT Devices Dataset

Comprehensive smart home dataset with 1,048,575 rows and 31 columns including timestamp, device states (TV, oven, lights, fridge) and activity labels for machine learning applications.

Feb 08, 2026
Smart Home Kaggle

Internet of Things Dataset for Home Renewable Energy Management

A synthetic but carefully constructed IoT dataset for smart home renewable energy management, providing five CSV datasets (20, 50, 100, 200 homes over 365 days) with daily energy consumption and production values to simulate small, medium, and large-scale smart city and smart home scenarios.

Feb 03, 2026
Smart Home Kaggle

2025 Competition on Electric Energy Consumption Forecasting - Smart Building Dataset

Multi-resolution smart building energy dataset for forecasting competition with three versions: 1-year at 5-min intervals (v1.0), 40-day at 5-min (v2.0), and 1-day hourly (v3.x), designed to benchmark state-of-the-art energy prediction techniques.

Feb 01, 2026
Smart Home Kaggle

Multi-Parameter Dataset for Machine Learning Based Environmental Spoilage Risk Assessment (Cold Storage IoT)

Cold storage monitoring dataset from IoT-enabled system designed for smallholder farmers in Uganda, featuring temperature, humidity, door events, and power status for training predictive models to classify environmental conditions and assess post-harvest food spoilage risk.

Jan 31, 2026

Explore other topics

All topics →