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,...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-08-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340923005024 |
| _version_ | 1797743972805771264 |
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| author | Ufuk Erol Francesco Raimondo James Pope Samuel Gunner Vijay Kumar Ioannis Mavromatis Pietro Carnelli Theodoros Spyridopoulos Aftab Khan George Oikonomou |
| author_facet | Ufuk Erol Francesco Raimondo James Pope Samuel Gunner Vijay Kumar Ioannis Mavromatis Pietro Carnelli Theodoros Spyridopoulos Aftab Khan George Oikonomou |
| author_sort | Ufuk Erol |
| collection | DOAJ |
| 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 |
| first_indexed | 2024-03-12T15:04:08Z |
| format | Article |
| id | doaj.art-26a66c9fd3c94be88b7f5dfc900481f8 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-03-12T15:04:08Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-26a66c9fd3c94be88b7f5dfc900481f82023-08-13T04:54:12ZengElsevierData in Brief2352-34092023-08-0149109392Multi-sensor, multi-device smart building indoor environmental datasetUfuk Erol0Francesco Raimondo1James Pope2Samuel Gunner3Vijay Kumar4Ioannis Mavromatis5Pietro Carnelli6Theodoros Spyridopoulos7Aftab Khan8George Oikonomou9University of Bristol, Bristol, UK; Corresponding authors.University of Bristol, Bristol, UK; Corresponding authors.University of Bristol, Bristol, UKUniversity of Bristol, Bristol, UKToshiba Europe Limited, Bristol Research and Innovation Laboratory, Bristol, UKToshiba Europe Limited, Bristol Research and Innovation Laboratory, Bristol, UKToshiba Europe Limited, Bristol Research and Innovation Laboratory, Bristol, UKCardiff University, Cardiff, UKToshiba Europe Limited, Bristol Research and Innovation Laboratory, Bristol, UKUniversity of Bristol, Bristol, UK; Corresponding authors.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/fwlmb11wni392kodtyljkw4n2http://www.sciencedirect.com/science/article/pii/S2352340923005024EnvironmentalInternet of ThingsData driftSensorSmart buildingTime series dataset |
| spellingShingle | Ufuk Erol Francesco Raimondo James Pope Samuel Gunner Vijay Kumar Ioannis Mavromatis Pietro Carnelli Theodoros Spyridopoulos Aftab Khan George Oikonomou Multi-sensor, multi-device smart building indoor environmental dataset Data in Brief Environmental Internet of Things Data drift Sensor Smart building Time series 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 | Environmental Internet of Things Data drift Sensor Smart building Time series dataset |
| url | http://www.sciencedirect.com/science/article/pii/S2352340923005024 |
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