Dataset of IoT-based energy and environmental parameters in a smart building infrastructure.

Autor:	Oulefki A; Smart Sustainable Cities Research Group (S2C), University of Sharjah, United Arab Emirates., Amira A; Smart Sustainable Cities Research Group (S2C), University of Sharjah, United Arab Emirates., Kurugollu F; Smart Sustainable Cities Research Group (S2C), University of Sharjah, United Arab Emirates., Soudan B; Smart Sustainable Cities Research Group (S2C), University of Sharjah, United Arab Emirates.
Jazyk:	angličtina
Zdroj:	Data in brief [Data Brief] 2024 Jul 29; Vol. 56, pp. 110769. Date of Electronic Publication: 2024 Jul 29 (Print Publication: 2024).
DOI:	10.1016/j.dib.2024.110769
Abstrakt:	This data article presents a detailed dataset collected as part of the University of Sharjah's (UoS) strategic initiative towards transforming into a smart campus by 2030. Collected from January 1st, 2024, to June 20nd, 2024, from key facilities including offices, labs, and communal spaces, the dataset encompasses precise energy consumption metrics and environmental conditions monitored via Internet of Things (IoT) sensors. It features appliance-specific power data (watts, voltage, kWh) alongside environmental parameters such as temperature, humidity, and occupancy rates. Distinctively, this dataset includes Markov Transition Field (MTF) visualizations, converting time series data into analytical 2D images, which facilitates advanced data interpretations suitable for Deep and transfer learning applications. Aimed at supporting research in energy management and intelligent system development, this dataset offers comprehensive insights into the operational dynamics of a transitioning smart campus, providing both raw and processed forms of data to accommodate diverse research needs. (© 2024 Published by Elsevier Inc.)
Databáze:	MEDLINE
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