IoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors.
Industry-standard dataset for prognostics research with simulated run-to-failure data from 100 turbofan engines including 21 sensor readings and remaining useful life (RUL) labels for predictive maintenance algorithms.
The most cited cybersecurity dataset worldwide with 2.8+ million network flows capturing 14 types of realistic attack scenarios including DDoS, brute force, botnet, and web attacks alongside benign traffic for advanced intrusion detection systems.
Comprehensive IoT network traffic dataset from an academic environment with 202,085 labeled records capturing benign and malicious activities for cybersecurity and anomaly detection research.
Real-time physiological and network-level data from a secure IoT healthcare monitoring system tracking 2000 patients, including biometric readings (heart rate, temperature, blood pressure) and network metadata for anomaly detection and cybersecurity analysis.
Real-time IoT sensor data from wearable health monitoring devices tracking patient vital signs including body temperature, blood pressure (systolic/diastolic), heart rate, and device battery levels for remote healthcare monitoring and predictive analytics.
Real-time IoT sensor data collected from industrial machines for predictive maintenance and anomaly detection in smart manufacturing environments, featuring temperature, vibration, pressure readings, and machine operational status for Industry 4.0 applications.
Simulated sensor data from IoT-based wearable healthcare devices monitoring vital signs including temperature, blood pressure, heart rate, and device battery levels for real-time remote patient monitoring and health analytics applications.
Comprehensive smart home dataset generated using OpenSHS simulator with 29 IoT sensors monitoring daily activities across multiple rooms, including labeled data for eating, sleeping, working, and anomaly detection in residential environments.
Real-time environmental dataset from IoT-enabled smart homes focusing on energy consumption optimization and occupant comfort, with 15-minute interval readings of temperature, humidity, lighting, air quality, CO2 levels, and HVAC control data.
Comprehensive dataset from Stratosphere Laboratory containing network traffic from 23 IoT malware captures including Mirai and Torii botnets, with over 325 million labeled connections for cybersecurity research and ML-based threat detection.