Dataset of IoT-based Energy and Environmental Parameters in a Smart Building Infrastructure

Overview

The Dataset of IoT-based energy and environmental parameters in a smart building infrastructure was collected as part of University of Sharjah's smart campus initiative and published in Data in Brief in 2024. It covers a mixed-use building with offices, meeting rooms, a kitchen, mail room, research labs, and lecture halls, monitored using IoT sensors.

Data Collection Setup

• Data was collected between January 1 and June 20, 2024 from a multi-purpose building on the University of Sharjah campus.
• Smart plugs and power meters monitor appliances such as a coffee machine, microwave, and refrigerator, capturing power, voltage, current, and cumulative energy.
• Environmental sensors record temperature, humidity, and room occupancy in labs, kitchen, mail room, and other key spaces.
• High-resolution time-series were stored in InfluxDB and later exported to CSV after aggregation and preprocessing.

Data Contents

• Raw time-series CSV files with timestamps and electrical measurements at appliance level.
• Environmental time-series capturing temperature, humidity, and occupancy indicators for different zones.
• Markov Transition Field (MTF) images representing time-series as 2D images for computer vision and deep learning approaches.
• Aggregated views that provide higher-level summaries of energy use and environmental conditions.

Value and Use Cases

• Supports research on building energy efficiency, smart building management, and AI-driven classification, anomaly detection, and recommender systems.
• Enables studies of appliance-level consumption patterns, waste detection, and evaluation of energy-saving strategies.
• Allows comparison of image-based deep learning models with traditional time-series approaches.

Access and License

The dataset is described in the Data in Brief article (volume 56, article 110769, DOI 10.1016/j.dib.2024.110769) with a public data repository on Zenodo that hosts raw and processed files and documentation. Data are available for research reuse under Elsevier and Zenodo terms, with proper citation.