Residential and commercial building sensor data: temperature, humidity, CO₂, occupancy, appliance-level consumption and home-automation event logs.
First open Zigbee IoT dataset with fully decrypted payloads from 15 real smart home devices over 20 days. CSV and PCAP formats. Published July 2025 on Zenodo. Used for Zigbee traffic analysis, device behavior modeling, and security research.
Free CC0 synthetic dataset: 1,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Cold Climate, 20.5°C.
Real smart-home IoT dataset from non-invasive PIR motion, magnetic door/window, and temperature sensors installed in multiple households. CSV format (6.4 MB). Used for occupancy detection, activity recognition, and smart home automation research.
Free CC0 synthetic dataset: 10,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Tropical Climate, 22°C.
Free CC0 synthetic dataset: 10,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Cold Climate, 22°C.
Free CC0 synthetic dataset: 2,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Arid Climate, 21°C. Reproducible from its seed.
Free CC0 synthetic dataset: 100 rows of indoor temperature, humidity, CO2, light and occupancy readings. 26.5°C. Reproducible from its seed.
Free CC0 synthetic dataset: 1,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Reproducible from its seed.
Comprehensive smart home dataset with 1,048,575 rows and 31 columns including timestamps, device states (TV, oven, lights, fridge) and activity labels for machine learning classification of daily activities.
Energy consumption readings from 5,567 London households participating in the UK Power Networks Low Carbon London project.
BCCC-IoT-IDS-Zwave-2025 is a behavior-centric cybersecurity dataset focusing on Z-wave protocol vulnerabilities and intrusion detection for modern smart home automation systems.
A real-world, hourly dataset of electricity, heating, and cooling consumption for a commercial building, ideal for benchmarking and building energy model calibration.
High-resolution, long-term historical data for solar photovoltaic (PV) and concentrated solar power (CSP) potential assessment anywhere on the globe.
A comprehensive, global dataset of hydropower plants, tracking their status, location, and capacity to support analysis of renewable energy infrastructure.
A high-resolution, three-year dataset from a real office building, integrating whole-building/end-use energy consumption, HVAC system data, environmental parameters, and ground-truth occupant counts. Essential for research in smart building energy prediction, optimization, and occupancy analytics.
Comprehensive smart home dataset with 1,048,575 rows and 31 columns including timestamp, device states (TV, oven, lights, fridge) and activity labels for machine learning applications.
Sensor recordings of activities by a single user in a smart home, using PIR, reed switches, force sensors, light, temperature/humidity and smart plugs; includes three CSV files for analysis.
Longitudinal ambient sensor data collected from 4 community homes featuring motion sensors, door sensors, and temperature readings with activity labels. This dataset captures naturalistic behavior patterns for activity recognition model development in real-world smart home environments. Data includes continuous recordings from PIR motion sensors, magnetic door sensors, and ambient temperature sensors with annotated activities by external annotators. The dataset provides a valuable resource for building activity recognition models that operate in uncontrolled, naturalistic settings.
ZigBeeNet is a novel smart home IoT dataset containing decrypted network traffic from 15 Zigbee devices, including smart lights and motion sensors, collected over a 20-day period. It provides rare access to decrypted payloads and network characteristics, making it ideal for researchers focused on traffic modeling, device behavior analysis, and the development of high-fidelity Zigbee traffic generators.
CeTI-Age-Kinematics is a full-body IMU kinematics dataset of 30 daily tasks recorded with a 19-IMU sensor suit in an age-comparative sample of 32 participants (older adults and younger controls), intended for motion analysis and activity recognition research.
GAITEX is a comprehensive multimodal human motion dataset capturing impaired gait and rehabilitation exercises using nine wearable IMUs and optical motion capture systems, designed for biomechanical analysis and rehabilitation monitoring.
DataSense is a real-time Industrial IoT (IIoT) dataset from the Canadian Institute for Cybersecurity, combining synchronized sensor and network data from a 40-device testbed with over 15 types of industrial sensors for anomaly and intrusion detection research.
MQTT_UAD is a public MQTT traffic dataset published in Data in Brief 2025, containing labeled benign and attack scenarios in IoT networks that use the MQTT protocol, designed for training and evaluating intrusion detection systems.
A real-world IoT dataset from a multi-purpose university building at University of Sharjah, capturing appliance-level energy consumption, temperature, humidity, and occupancy, along with 2D Markov Transition Field (MTF) image representations for deep learning, published in Data in Brief.