iPhone 6s accelerometer and gyroscope dataset from 24 subjects performing 6 activities (walking, jogging, stairs up/down, sitting, standing) at 50 Hz. CSV. Kaggle and GitHub. Used for human activity recognition (HAR) and mobile sensor privacy research. Imperial College London, 2018.
Comprehensive energy dataset from 255 UK homes covering electricity, gas, room temperature, humidity, and appliance-level data for a 39-home sub-cohort. 23 months of data. CSV format. Published on Edinburgh DataShare (DOI: 10.7488/ds/2836). Described in Nature Scientific Data 2021.
Real IoT smart home energy dataset from a testbed of 5 household appliances each connected to an individual smart meter. 507 KB CSV. Published January 2025 on Zenodo. Used for appliance-level energy monitoring, household energy disaggregation, and smart meter analytics.
Anonymised smart meter electricity consumption data from the CKW Group distribution network in Lucerne Canton, Switzerland. 15-minute resolution, covering 2021–2024. Parquet and CSV formats. Published on Zenodo 2024. Used for large-scale household energy analytics and smart grid research.
Longest freely available on-field IoT air quality sensor deployment: 9,358 hourly records from 5 metal oxide gas sensors in an Italian city. CSV/XLSX format. Used for gas sensor regression, drift correction, and pollution forecasting research.
Open urban sensing dataset from 130 IoT nodes across Chicago measuring temperature, humidity, pressure, light, CO, NOâ‚‚, SOâ‚‚, ozone, sound, and pedestrian/vehicle traffic. CSV via Chicago Open Data Portal. Used for smart city analytics and urban environment research.
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.
NASA Prognostics Center run-to-failure simulation dataset for turbofan engines. Four operational sub-datasets with 21 sensor channels and 3 operational settings. TXT/CSV format. Primary benchmark for Remaining Useful Life (RUL) estimation.
Benchmark bearing vibration dataset from Case Western Reserve University with drive-end and fan-end faults at 4 severity levels. Sampled at 12 kHz and 48 kHz. MATLAB MAT and CSV formats. Used for fault diagnosis and vibration-based condition monitoring.
Synthetic IIoT dataset reflecting real milling machine predictive maintenance scenarios. 10,000 records with 14 features including air temperature, process temperature, rotational speed, torque, and 5 labeled failure types. CSV format. Ideal for multi-label fault classification.
Real-world IIoT multivariate time series dataset tracking physicochemical degradation of metalworking fluid over several months. Includes imputed benchmark variants for 5 methods. CSV format. Designed for predictive maintenance and anomaly detection research in manufacturing.