Collection of real-world smart city IoT datasets from the CityPulse project, including vehicle traffic, parking occupancy, and weather data from Aarhus (Denmark) and other cities.[web:111][web:114][web:116]
Real smart-home energy consumption data (10-minute resolution) with indoor room sensors and outdoor weather measurements, designed to model appliance energy use in a low-energy house.[web:55][web:61][web:66]
Curated machine-learning-ready dataset from NASA’s Solar Dynamics Observatory (SDO) mission integrating multiple solar instruments for flare prediction and solar activity modeling.
Fused Level-1 radiances from all five instruments on NASA’s Terra satellite (MODIS, MISR, MOPITT, CERES, ASTER) from 2000–2015 for advanced Earth system and climate analytics.
AllWISE combines all WISE mission phases into a full-sky mid‑infrared survey with 18,240 FITS image sets and a catalog of ~747 million sources at 3.4, 4.6, 12, and 22 μm.
Infrared survey data from the reactivated NEOWISE mission with >20 million calibrated FITS images in two bands (W1, W2). Essential for asteroid and comet discovery and thermal modeling.
Specialized dataset containing features influencing vehicle collisions in Internet of Vehicles (IoV) networks. Includes V2V communication data, sensor readings, traffic conditions, and collision indicators for developing intelligent collision detection and prevention systems.
Large-scale real-time air quality monitoring dataset from Dhaka, Bangladesh with 155,406 records. Captures CO, NO2, SO2, O3, PM2.5, and PM10 using IoT sensors with Arduino integration. Ideal for environmental analytics, pollution prediction, and smart city air quality management.
Two years of continuous IoT-based smart parking lot usage data collected via ThingSpeak platform. Features IR sensors and ESP32 boards monitoring slot availability, occupancy patterns, peak hours, and parking duration for urban parking management optimization.
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.