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.
First open Zigbee IoT dataset with fully decrypted payloads, captured from a real smart home with 15 Zigbee devices over 20 days. Distributed as a single archive (dataset.tar.gz, 663.4 MB) of pcap captures with the network key included. Published October 2024 on Zenodo under CC BY 4.0.
Wearable IoT dataset with 18 physical activities from 9 subjects wearing 3 IMUs and a heart rate monitor. 54 columns including temperature, acceleration, and gyroscope data. CSV format. Used for HAR, activity classification, and intensity estimation.
Network-traffic dataset on Mendeley Data documenting DDoS attacks against the Fibaro Home Center 3 smart-home controller; PCAP and CSV formats are provided. [page:4][web:52]
An MQTT DoS and DDoS IoT attack dataset collected on a Raspberry Pi 3B+ Mosquitto broker over 12 sessions, including three days of normal traffic and several minutes of attack traffic, totaling 424,716 labeled entries for machine learning-based IDS and IPS research.
A real-world IoT dataset from a multi-purpose university building at University of Sharjah, capturing appliance-level energy consumption, temperature, humidity, and occupancy, along with 2D Markov Transition Field (MTF) image representations for deep learning, published in Data in Brief.
Cold storage monitoring dataset from IoT-enabled system designed for smallholder farmers in Uganda, featuring temperature, humidity, door events, and power status for training predictive models to classify environmental conditions and assess post-harvest food spoilage risk.
Real-world dataset from International University of Rabat for threat detection in MQTT-IoT networks, containing actual cyberattacks executed on MySignals health sensors.