Multi-sensor, Multi-device Smart Building Indoor Environmental Dataset

Ufuk Erol, Francesco Raimondo, James Pope, Sam D Gunner, Vijay Kumar, Ioannis Mavromatis, Pietro Carnelli, Theodoros Spyridopoulos, Aftab Khan, George Oikonomou

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

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
Original languageEnglish
Article number109392
JournalData in Brief
Volume49
DOIs
Publication statusPublished - 14 Jul 2023

Bibliographical note

Funding Information:
This work was supported by UK Research and Innovation , Innovate UK [grant number 53707 ].

Publisher Copyright:
© 2023

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