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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,...

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Autores principales: Erol, Ufuk, Raimondo, Francesco, Pope, James, Gunner, Samuel, Kumar, Vijay, Mavromatis, Ioannis, Carnelli, Pietro, Spyridopoulos, Theodoros, Khan, Aftab, Oikonomou, George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
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
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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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