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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 f...

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Detalles Bibliográficos
Autores principales: Jacoby, Margarite, Tan, Sin Yong, Henze, Gregor, Sarkar, Soumik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553852/
https://www.ncbi.nlm.nih.gov/pubmed/34711840
http://dx.doi.org/10.1038/s41597-021-01055-x
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author Jacoby, Margarite
Tan, Sin Yong
Henze, Gregor
Sarkar, Soumik
author_facet Jacoby, Margarite
Tan, Sin Yong
Henze, Gregor
Sarkar, Soumik
author_sort Jacoby, Margarite
collection PubMed
description 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.
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spelling pubmed-85538522021-10-29 A high-fidelity residential building occupancy detection dataset Jacoby, Margarite Tan, Sin Yong Henze, Gregor Sarkar, Soumik Sci Data Data Descriptor 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. Nature Publishing Group UK 2021-10-28 /pmc/articles/PMC8553852/ /pubmed/34711840 http://dx.doi.org/10.1038/s41597-021-01055-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Jacoby, Margarite
Tan, Sin Yong
Henze, Gregor
Sarkar, Soumik
A high-fidelity residential building occupancy detection dataset
title A high-fidelity residential building occupancy detection dataset
title_full A high-fidelity residential building occupancy detection dataset
title_fullStr A high-fidelity residential building occupancy detection dataset
title_full_unstemmed A high-fidelity residential building occupancy detection dataset
title_short A high-fidelity residential building occupancy detection dataset
title_sort high-fidelity residential building occupancy detection dataset
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553852/
https://www.ncbi.nlm.nih.gov/pubmed/34711840
http://dx.doi.org/10.1038/s41597-021-01055-x
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