Multimodal smart city dataset combining environmental sensors (temperature, humidity, gas, vibration, noise, motion) and surveillance images with binary anomaly labels. Designed for edge computing, urban anomaly detection, and real-time city monitoring research.
Multivariate dataset exploring the integration of IoT sensor data with AI algorithms across multiple domains. Features diverse sensor types, environmental parameters, and AI model performance metrics for hybrid intelligent systems research.
Novel dataset combining IoT environmental sensors with robotic vision for automated plant disease detection. Published in Nature Scientific Reports January 2026. Features leaf images, environmental parameters, and deep learning disease classification with 98.9% accuracy.
Real-world IoT sensor dataset for precision agriculture and plant health monitoring. Includes environmental parameters (temperature, humidity, light) and soil metrics (pH, moisture, temperature) with Arduino-ESP8266 integration and cloud transmission.
IoT-based environmental perception data studying impact on university students' mental health. Integrates temperature, humidity, noise, and air quality sensors.
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.
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 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.
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).