Industrial IoT IDS dataset with labelled TCP/IP and DNP3 flow statistics plus PCAP files for 9 SCADA cyberattacks. CSV and PCAP formats for ML/DL IDS research.
MQTT IoT IDS dataset from a simulated network with 12 sensors, broker, camera, and attacker. PCAP and CSV features support MQTT intrusion detection research.
IoT botnet IDS dataset using 83 real and emulated devices with Mirai, BashLite, and Torii traffic. Raw PCAP files support botnet and anomaly detection research.
IoT IDS dataset for distinguishing normal and malicious ICMP/Ping traffic generated from an ESP-01s embedded device. PCAP, Zeek logs, and labelled CSV files.
Real-time posture monitoring dataset from the MPU6050 6-axis sensor (3D gyroscope + 3D accelerometer) attached to the upper body, streaming wirelessly via Phyphox. Angular orientation values: Angle_X, Angle_Y, Angle_Z. Mendeley Data, March 2025 — DOI: 10.17632/ftn4rjnd6x.1. Used for LSTM-based posture classification and ergonomics.
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.
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.
Novel multimodal HAR dataset for basketball training with synchronized IMU (accelerometer, gyroscope, angle, magnetic field at 200 Hz, MPU9250/WT901) + heart rate and skin surface temperature (1 Hz, Si1141 wrist sensor) across 14 activity classes. ArXiv 2025. Used for sports performance analysis and LLM-based coaching reports.
Free CC0 synthetic dataset: 4,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 21% Attacks. Reproducible from its seed.
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.