A real-world IoT dataset from a multi-purpose university building at University of Sharjah, capturing appliance-level energy consumption, temperature, humidity, and occupancy, along with 2D Markov Transition Field (MTF) image representations for deep learning, published in Data in Brief.
Massive dataset from solar panels, wind turbines, and smart grid infrastructure for energy forecasting, demand prediction, and efficiency optimization using big data analytics, machine learning, Hadoop, and Spark distributed processing frameworks.
Detailed energy monitoring dataset from smart home testbed with five common household appliances (refrigerator, washing machine, microwave, air conditioner, TV) each connected to individual smart meters for appliance-level consumption analysis and NILM research.
Multi-resolution smart building energy dataset for forecasting competition with three versions: 1-year at 5-min intervals (v1.0), 40-day at 5-min (v2.0), and 1-day hourly (v3.x), designed to benchmark state-of-the-art energy prediction techniques.
Standardized energy flexibility data model enabling uniform communication of energy flexibility potentials within industrial companies and in exchange with external energy systems (grids, aggregators), supporting demand response and sector coupling.
Multimodal dataset from 24 participants with synchronized wrist-worn PPG from Galaxy Watch 5 and Empatica E4, plus chest ECG from Polar H10, collected during diverse activities in semi-naturalistic settings for evaluating consumer-grade wearable performance.
Real operational electricity system records from ISO New England (ISONE) covering urban smart city energy activity including demand, generation, pricing, and grid operations across multiple metropolitan areas for energy analytics and forecasting.
Multimodal dataset combining Text-to-SQL natural language queries with IoT network traffic classification, featuring 10,985 SQL training examples and labeled network traffic (benign/malicious) from IoT-23 and Smart Building sensors for NLP and security research.
Curated collection of 10,000+ realistic IoT sensor readings from Bangladesh representing diverse environmental conditions including temperature, humidity, soil moisture, rainfall, and air quality with timestamps and location tags for smart agriculture and climate research.
Comprehensive multi-sensor dataset with 9 parameters including environmental (temperature, humidity, light) and soil measurements (moisture, temperature, pH) plus solar battery voltage and water TDS, collected via Arduino-ESP8266 system with cloud integration.
Cold storage monitoring dataset from IoT-enabled system designed for smallholder farmers in Uganda, featuring temperature, humidity, door events, and power status for training predictive models to classify environmental conditions and assess post-harvest food spoilage risk.
Wearable IMU dataset from 22 Parkinson's disease patients performing standardized motor tasks, with four inertial sensors (ankles, wrist, lower back) capturing freezing of gait (FoG) episodes, designed for algorithm development and clinical gait analysis.