IoT Environmental Monitoring - Student Mental Health Dataset
IoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors.
View DatasetShowing 12 of 119 datasets
IoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors.
View DatasetIndustry-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.
View DatasetReal-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.
View DatasetComprehensive Industrial IoT dataset simulating real-time edge computing scenarios with sensor data, network latency metrics, Fuzzy PID controller outputs, and predictive failure labels for smart manufacturing and autonomous decision-making research.
View DatasetReal-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.
View DatasetComprehensive 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.
View DatasetReal-world dataset from International University of Rabat for threat detection in MQTT-IoT networks, containing actual cyberattacks executed on MySignals health sensors.
View DatasetReal-time supply chain data from IoT sensors across logistics stages. Includes GPS tracking, RFID inventory, environmental sensors, supplier performance metrics, and delivery patterns for predictive analysis.
View DatasetIoT sensor data from smart building systems for energy management. Contains real-time power consumption, HVAC operations, lighting control, and appliance-level energy disaggregation data.
View DatasetTelemetry from smart plugs monitoring individual household appliances. Used for identifying energy-hungry devices and predictive load balancing.
View DatasetReal-world data from a metro train's Air Production Unit (APU), capturing pressure, temperature, and motor current to predict component failures.
View DatasetA comprehensive augmented dataset containing 60,000 observations for predicting electrical grid stability in decentralized smart grid control (DSGC) systems. Ideal for testing binary classification algorithms and deep learning models in energy management.
View Dataset