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.
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.
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.
Reproducible large-scale IoT network dataset from 78 emulated devices using MQTT, CoAP, and RTSP protocols. Includes benign and malicious traffic with DoS, brute force, scanning, and C&C attacks in PCAP and CSV formats.
Comprehensive smart home dataset with 1,048,575 rows and 31 columns including timestamps, device states (TV, oven, lights, fridge) and activity labels for machine learning classification of daily activities.
CeTI-Age-Kinematics is a full-body IMU kinematics dataset of 30 daily tasks recorded with a 19-IMU sensor suit in an age-comparative sample of 32 participants (older adults and younger controls), intended for motion analysis and activity recognition research.
GAITEX is a comprehensive multimodal human motion dataset capturing impaired gait and rehabilitation exercises using nine wearable IMUs and optical motion capture systems, designed for biomechanical analysis and rehabilitation monitoring.
A multi-sensor dataset from a real manufacturing environment monitoring CNC machine degradation through vibration, temperature, current, and acoustic emission sensors over a 6-month period.
MQTT_UAD is a public MQTT traffic dataset published in Data in Brief 2025, containing labeled benign and attack scenarios in IoT networks that use the MQTT protocol, designed for training and evaluating intrusion detection systems.
DataSense is a real-time Industrial IoT (IIoT) dataset from the Canadian Institute for Cybersecurity, combining synchronized sensor and network data from a 40-device testbed with over 15 types of industrial sensors for anomaly and intrusion detection research.
A real-world MQTT-based IoT cybersecurity dataset collected from the MQTTEEB testbed at the International University of Rabat, with benign traffic and five attack types (DoS, SlowITe, Malformed Data Injection, Brute Force, Publish Flooding), provided in multiple processed forms (raw, cleaned, normalized, standardized, SMOTE) for AI-driven intrusion detection research.