Smart-home energy dataset with detailed electrical, environmental, and operational streams from 3 real homes plus minute-level electricity data from 400+ homes. Open portal export format. Used for sustainable home and demand analysis.
Long-duration smart-home utility dataset with two years of minutely electricity, water, and natural gas measurements plus weather and billing data. CSV/TSV/RData formats. Used for forecasting, NILM, and resource analytics.
Open-access domestic electricity dataset from 5 UK homes with whole-house demand at 16 kHz and appliance channels at 6-second intervals. Research-paper dataset release. Used for NILM, load disaggregation, and smart-meter analytics.
MIMIC-III is a globally recognized database featuring de-identified health data from 40,000+ ICU patients, integrating vital signs, lab results, and IoT device outputs for research.
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.
A dataset capturing real-time metrics of resource allocation and workload distribution across multi-tier IoT architectures. Includes latency, CPU and memory usage, task execution times, and predictive performance variables, enabling research in IoT resource management, edge analytics and performance optimization.
The Industrial IoT Dataset (Synthetic) provides a large-scale simulation of sensor readings and operational metrics from machines deployed in a smart factory environment. It focuses on predictive maintenance and anomaly detection.
Large-scale real-time air quality monitoring dataset from Dhaka, Bangladesh with 155,406 records. Captures CO, NO2, SO2, O3, PM2.5, and PM10 using IoT sensors with Arduino integration. Ideal for environmental analytics, pollution prediction, and smart city air quality management.
Multimodal smart city dataset combining environmental sensors (temperature, humidity, gas, vibration, noise, motion) and surveillance images with binary anomaly labels. Designed for edge computing, urban anomaly detection, and real-time city monitoring research.