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 comprehensive and realistic IoT dataset generated by the Canadian Institute for Cybersecurity (CIC) for profiling, detecting, and characterizing multi-vector IoT attacks in a real network topology.
A comprehensive, high-quality dataset from a network of ground monitoring stations across Saudi Arabia, measuring solar radiation components, wind resources, and related meteorological parameters. Essential for renewable energy feasibility studies, smart grid planning, and machine learning models in energy forecasting.
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.
Open-source GitHub repository featuring curated collection of 25+ datasets for deep learning applications in IoT including Gas Sensor Array Drift, ISOLET, Sleep-EDF, and comprehensive benchmark datasets under MIT license for unrestricted research use.
Industrial IoT dataset for efficient monitoring and control of power generation and distribution processes in smart grid applications with real-time fault detection capabilities.
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.
Dataset documents replay attacks targeting MQTT communications in water distribution system with 4.8 MB CSV file containing original and replayed messages for temporal sequence analysis.
IoT-23 provides labeled IoT network-traffic captures, including 20 malware scenarios and 3 benign IoT captures, intended to support machine-learning research on IoT security.
Public (anonymized) predictive maintenance datasets from Huawei Munich Research Center for elevator industry; operation time series sampled at 4Hz (16:30–23:30) using electromechanical sensors, humidity, and vibration.
A real-world cybersecurity dataset capturing MQTT-based IoT network traffic with live attacks and anomalous behavior. Collected from an active deployment with multiple attack types including DoS, SlowITe, and malformed injections. Provides both raw and preprocessed CSV files with rich metadata for intrusion detection and anomaly classification research.