Multi-site IMU dataset (chest, hands, knees) with heart rate and SpO2 recorded at 0.5 Hz during structured daily activities and a 3-minute step test. Raw + preprocessed IMU (accelerometer, gyroscope, quaternions) + demographic metadata. Zenodo, July 2025. Used for cardiorespiratory fitness (CRF) estimation and HAR.
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.
Massive dataset from solar panels, wind turbines, and smart grid infrastructure for energy forecasting, demand prediction, and efficiency optimization using big data analytics, machine learning, Hadoop, and Spark distributed processing frameworks.
Detailed energy monitoring dataset from smart home testbed with five common household appliances (refrigerator, washing machine, microwave, air conditioner, TV) each connected to individual smart meters for appliance-level consumption analysis and NILM research.
Multi-resolution smart building energy dataset for forecasting competition with three versions: 1-year at 5-min intervals (v1.0), 40-day at 5-min (v2.0), and 1-day hourly (v3.x), designed to benchmark state-of-the-art energy prediction techniques.
Standardized energy flexibility data model enabling uniform communication of energy flexibility potentials within industrial companies and in exchange with external energy systems (grids, aggregators), supporting demand response and sector coupling.
Multimodal dataset combining Text-to-SQL natural language queries with IoT network traffic classification, featuring 10,985 SQL training examples and labeled network traffic (benign/malicious) from IoT-23 and Smart Building sensors for NLP and security research.
Industrial sensor dataset for predictive maintenance research featuring real-time sensor data and historical equipment records from smart manufacturing systems, enabling machine learning models (decision trees, neural networks) to forecast equipment failures and optimize maintenance scheduling.
Comprehensive collection of research papers on IoT attacks and security models published between 2005-2025 in IEEE, Elsevier, Springer, ACM, and MDPI, compiled for systematic review of IoT network security across all layers, enabling meta-analysis and trend identification.
Large-scale reproducible IoT network dataset with traffic from 100+ diverse IoT devices including smart home, wearable, and industrial sensors, featuring multiple attack scenarios and benign behavior for intrusion detection research.
Complete and labeled IoT dataset from physical data center with NFC smart passive temperature sensors, containing normal operations and anomalous behaviors for time-series anomaly detection in critical infrastructure environments.