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

TL;DR

This paper presents a comprehensive year-long indoor environment dataset from three US single-family houses, including temperature, humidity, air quality, and noise data, to support building performance research.

Contribution

It introduces a detailed, high-frequency dataset with sensor placements and verification methods, enabling improved modeling of indoor environmental conditions.

Findings

Over 2.5 million records collected

Dataset covers diverse indoor environmental factors

Provides floor plans and sensor placement details

Abstract

The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data was 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 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.