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.
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.
Dataset for evaluating federated learning approaches to IoT intrusion detection published in Nature Scientific Reports January 2026. Features distributed network traffic from multiple IoT deployments with privacy constraints and decentralized learning evaluation metrics.