A high-fidelity residential building occupancy detection dataset

This paper describes development of a data acquisition system used to capture a range of occupancy related modalities from single-family residences, along with the dataset that was generated. The publicly available dataset includes: grayscale images at 32-by-32 pixels, captured every second; audio files, which have undergone processing to remove personally identifiable information; indoor environmental readings, captured every ten seconds; and ground truth binary occupancy status. The data acquisition system, coined the mobile human presence detection (HPDmobile) system, was deployed in six homes for a minimum duration of one month each, and captured all modalities from at least four different locations concurrently inside each home. The environmental modalities are available as captured, but to preserve the privacy and identity of the occupants, images were downsized and audio files went through a series of processing steps, as described in this paper. This dataset adds to a very small body of existing data, with applications to energy efficiency and indoor environmental quality. Measurement(s) room temperature ambient air • room air relative humidity • Carbon Dioxide • total volatile organic compounds • room illuminance • Audio Media • Digital Photography • Occupancy Technology Type(s) Thermostat Device • humidity sensor • gas sensor • light sensor • Microphone Device • Camera Device • manual recording Sample Characteristic - Environment residential building Sample Characteristic - Location United States of America Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14920131