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Multi-sensor, multi-device smart building indoor environmental dataset
A dataset of sensor measurements is presented. Our dataset contains discrete measurements of 8 IoT devices located in various places in a research lab at the University of Bristol. Nordic nRF52840 DK IoT devices periodically collects environmental data, such as temperature, humidity, pressure, gas,...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375552/ https://www.ncbi.nlm.nih.gov/pubmed/37520650 http://dx.doi.org/10.1016/j.dib.2023.109392 |
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author | Erol, Ufuk Raimondo, Francesco Pope, James Gunner, Samuel Kumar, Vijay Mavromatis, Ioannis Carnelli, Pietro Spyridopoulos, Theodoros Khan, Aftab Oikonomou, George |
author_facet | Erol, Ufuk Raimondo, Francesco Pope, James Gunner, Samuel Kumar, Vijay Mavromatis, Ioannis Carnelli, Pietro Spyridopoulos, Theodoros Khan, Aftab Oikonomou, George |
author_sort | Erol, Ufuk |
collection | PubMed |
description | A dataset of sensor measurements is presented. Our dataset contains discrete measurements of 8 IoT devices located in various places in a research lab at the University of Bristol. Nordic nRF52840 DK IoT devices periodically collects environmental data, such as temperature, humidity, pressure, gas, room light intensity, accelerometer; including also a measurement quality indicator. The measurements were taken every 10 seconds over a six-month period between February and September 2022. In addition, we provide Received Signal Strength Indicator (RSSI) of the IoT devices. The data files are formatted as CSV files. There are various software libraries available to access and read this file format. We provide “README.txt” file which explains the repository and how to use dataset. Each data file is named according to its creation date and, once it reaches a size of 1MB, it is compressed and archived. A new folder is created every week to store all the data files from that week automatically. The dataset can be used for drift detection such as malicious or anomaly detection algorithms. It can also be used for smart building applications like occupation detection. The dataset can be found at https://data.bris.ac.uk/data/dataset/fwlmb11wni392kodtyljkw4n2 |
format | Online Article Text |
id | pubmed-10375552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103755522023-07-29 Multi-sensor, multi-device smart building indoor environmental dataset Erol, Ufuk Raimondo, Francesco Pope, James Gunner, Samuel Kumar, Vijay Mavromatis, Ioannis Carnelli, Pietro Spyridopoulos, Theodoros Khan, Aftab Oikonomou, George Data Brief Data Article A dataset of sensor measurements is presented. Our dataset contains discrete measurements of 8 IoT devices located in various places in a research lab at the University of Bristol. Nordic nRF52840 DK IoT devices periodically collects environmental data, such as temperature, humidity, pressure, gas, room light intensity, accelerometer; including also a measurement quality indicator. The measurements were taken every 10 seconds over a six-month period between February and September 2022. In addition, we provide Received Signal Strength Indicator (RSSI) of the IoT devices. The data files are formatted as CSV files. There are various software libraries available to access and read this file format. We provide “README.txt” file which explains the repository and how to use dataset. Each data file is named according to its creation date and, once it reaches a size of 1MB, it is compressed and archived. A new folder is created every week to store all the data files from that week automatically. The dataset can be used for drift detection such as malicious or anomaly detection algorithms. It can also be used for smart building applications like occupation detection. The dataset can be found at https://data.bris.ac.uk/data/dataset/fwlmb11wni392kodtyljkw4n2 Elsevier 2023-07-14 /pmc/articles/PMC10375552/ /pubmed/37520650 http://dx.doi.org/10.1016/j.dib.2023.109392 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Erol, Ufuk Raimondo, Francesco Pope, James Gunner, Samuel Kumar, Vijay Mavromatis, Ioannis Carnelli, Pietro Spyridopoulos, Theodoros Khan, Aftab Oikonomou, George Multi-sensor, multi-device smart building indoor environmental dataset |
title | Multi-sensor, multi-device smart building indoor environmental dataset |
title_full | Multi-sensor, multi-device smart building indoor environmental dataset |
title_fullStr | Multi-sensor, multi-device smart building indoor environmental dataset |
title_full_unstemmed | Multi-sensor, multi-device smart building indoor environmental dataset |
title_short | Multi-sensor, multi-device smart building indoor environmental dataset |
title_sort | multi-sensor, multi-device smart building indoor environmental dataset |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375552/ https://www.ncbi.nlm.nih.gov/pubmed/37520650 http://dx.doi.org/10.1016/j.dib.2023.109392 |
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