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.
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 energy consumption dataset from a smart home with detailed weather information, containing readings from 17 different appliances and devices with 13 weather parameters for advanced consumption forecasting.
Comprehensive dataset from University of New Brunswick containing over 202,085 network traffic records from IoT devices in academic environment, with classification of benign and malicious activities.
Six months of IoT sensor data from tilapia aquaculture ponds in Colombia. Monitors dissolved oxygen, pH, temperature, turbidity with fish health metrics (weight, survival rate, disease occurrence).
Real-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.
Dataset for analyzing dynamic optimization techniques impact on energy efficiency in IoT sensor networks. Contains 500 simulation scenarios with routing protocols comparison and performance metrics.