A Comprehensive Indoor Environment Dataset from Single-Family Houses in the US

The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data were collected from 10 sensing devices installed in various locations within three single-family houses in Virginia, USA. The objective of the data collection was to study the indoor environmental conditions of the houses over time. The data were collected at a frequency of one record per minute for a year, combining to a total over 2.5 million records. The paper provides actual floor plans with sensor placements to aid researchers and practitioners in creating reliable building performance models. The techniques used to collect and verify the data are also explained in the paper. The resulting dataset can be employed to enhance models for building energy consumption, occupant behavior, predictive maintenance, and other relevant purposes.

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Journal
Data
Published
2025-03-05
DOI
https://doi.org/10.3390/data10030035
Citations
1
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.01
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article

A Comprehensive Indoor Environment Dataset from Single-Family Houses in the US

Sheik Murad Hassan Anik, Xinghua Gao, Na Meng
1 citations
Data
Building Energy and Comfort Optimization
1.01
article

A Comprehensive Indoor Environment Dataset from Single-Family Houses in the US

Sheik Murad Hassan Anik, Xinghua Gao, Na Meng
article en
1 citations

Abstract

The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data were collected from 10 sensing devices installed in various locations within three single-family houses in Virginia, USA. The objective of the data collection was to study the indoor environmental conditions of the houses over time. The data were collected at a frequency of one record per minute for a year, combining to a total over 2.5 million records. The paper provides actual floor plans with sensor placements to aid researchers and practitioners in creating reliable building performance models. The techniques used to collect and verify the data are also explained in the paper. The resulting dataset can be employed to enhance models for building energy consumption, occupant behavior, predictive maintenance, and other relevant purposes.

DataVol. 10(3)
Virginia Tech (US), Auburn University at Montgomery (US)
Openalex Percentile: Top 27%
Building Energy and Comfort Optimization
1.01
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A Comprehensive Indoor Environment Dataset from Single-Family Houses in the US — Sheik Murad Hassan Anik, Xinghua Gao, et al. · Data (2025) | TGRS Research Map | TGRS