Published in November 2025, this dataset provides a multimodal framework integrating satellite imagery and IoT sensor data for environmental monitoring and disaster management. It is designed to support the development of machine learning models that synchronize remote sensing with ground-based IoT observations for real-time risk assessment.
AIR4LIFE is a high-resolution air quality monitoring dataset published in late 2025, featuring measurements from a dual-node IoT setup. It tracks pollutants and ambient conditions to evaluate the trade-offs between energy-aware duty cycling and data completeness in environmental sensing networks.
UrbanAirNet provides a comprehensive collection of urban air quality and weather parameters measured via IoT sensor networks. It includes pollutants like PM2.5, NO2, and O3 alongside meteorological variables.
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.
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.
Dataset documenting IoT sensor deployments in horticulture operations including greenhouse monitoring, fruit/vegetable cultivation parameters, and automated control systems for temperature, humidity, light, and nutrient delivery.
Spatio-temporal water quality dataset from 36 monitoring sites in Georgia, USA, with 11 indices including dissolved oxygen, temperature, conductance, and pH for daily forecasting of pH levels.
Hourly air pollutant measurements (PM2.5, PM10, SO₂, NO₂, CO, O₃) and meteorological data from 12 nationally controlled monitoring sites in Beijing, collected from March 2013 to February 2017 (420,768 instances).[page:1][web:74]
Smart-building dataset from the M5 building, including appliance-level energy usage (watts, voltage, kWh) plus temperature, humidity, and occupancy measurements in offices, labs, kitchen, and other spaces.[web:164][web:167][web:170]
Long-term laboratory recordings from a 16-sensor chemical gas array exposed to six different gases across multiple batches, designed to study sensor drift and robustness of gas classification models.[web:87][web:89][web:95][web:104]
City-scale environmental IoT dataset with more than 24 million temperature measurements from SmartSantander sensors deployed across Santander, Spain, including spatial, temporal, and device metadata.[web:113][web:115][web:118]
Real-world hourly air quality measurements from an array of chemical gas sensors deployed at road level in a polluted Italian city, collected from March 2004 to February 2005.[web:46][web:53][web:77]