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PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications

The current cost that energy represents is crucial in a field like climate control which has high energy demands, therefore its reduction must be prioritized. The expansion of ICT and IoT come with an extensive deployment of sensors and computation infrastructure creating an opportunity to analyze a...

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Autores principales: Ibarra, Antonio Martínez, González-Vidal, Aurora, Skarmeta, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984460/
https://www.ncbi.nlm.nih.gov/pubmed/36869087
http://dx.doi.org/10.1038/s41597-023-02023-3
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author Ibarra, Antonio Martínez
González-Vidal, Aurora
Skarmeta, Antonio
author_facet Ibarra, Antonio Martínez
González-Vidal, Aurora
Skarmeta, Antonio
author_sort Ibarra, Antonio Martínez
collection PubMed
description The current cost that energy represents is crucial in a field like climate control which has high energy demands, therefore its reduction must be prioritized. The expansion of ICT and IoT come with an extensive deployment of sensors and computation infrastructure creating an opportunity to analyze and optimize energy management. Data on building internal and external conditions is essential for developing efficient control strategies in order to minimize energy consumption while maintaining users’ comfort inside. We here present a dataset that provides key features that could be useful for a wide range of applications in the context of modeling temperature and consumption via Artificial Intelligence algorithms. The data gathering has taken place for almost 1 year in the Pleiades building of the University of Murcia, which is a pilot building of the European project PHOENIX aiming to improve building energy efficiency.
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spelling pubmed-99844602023-03-05 PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications Ibarra, Antonio Martínez González-Vidal, Aurora Skarmeta, Antonio Sci Data Data Descriptor The current cost that energy represents is crucial in a field like climate control which has high energy demands, therefore its reduction must be prioritized. The expansion of ICT and IoT come with an extensive deployment of sensors and computation infrastructure creating an opportunity to analyze and optimize energy management. Data on building internal and external conditions is essential for developing efficient control strategies in order to minimize energy consumption while maintaining users’ comfort inside. We here present a dataset that provides key features that could be useful for a wide range of applications in the context of modeling temperature and consumption via Artificial Intelligence algorithms. The data gathering has taken place for almost 1 year in the Pleiades building of the University of Murcia, which is a pilot building of the European project PHOENIX aiming to improve building energy efficiency. Nature Publishing Group UK 2023-03-03 /pmc/articles/PMC9984460/ /pubmed/36869087 http://dx.doi.org/10.1038/s41597-023-02023-3 Text en © The Author(s) 2023 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/) .
spellingShingle Data Descriptor
Ibarra, Antonio Martínez
González-Vidal, Aurora
Skarmeta, Antonio
PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title_full PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title_fullStr PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title_full_unstemmed PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title_short PLEIAData: consumption, HVAC, temperature, weather and motion sensor data for smart buildings applications
title_sort pleiadata: consumption, hvac, temperature, weather and motion sensor data for smart buildings applications
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984460/
https://www.ncbi.nlm.nih.gov/pubmed/36869087
http://dx.doi.org/10.1038/s41597-023-02023-3
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