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]
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.
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.
State-of-the-art IIoT dataset from Canadian Institute for Cybersecurity with synchronized sensor and network data from 40 devices including 15+ industrial sensors. Features multi-objective feature selection for anomaly detection in industrial environments.
Comprehensive large-scale IoT botnet dataset combining legitimate IoT network traffic with realistic botnet attack scenarios. Features full packet captures (PCAP) and extracted flow features for diverse attack types including DDoS, reconnaissance, theft, and DoS attacks.
Comprehensive large-scale IoT intrusion detection dataset from Canadian Institute for Cybersecurity with 33 attack types across 105 real IoT devices. Includes 8.94 GB of network traffic data covering DDoS, DoS, Mirai, MITM, and reconnaissance attacks.
Enhanced smart home energy consumption dataset with minute-resolution monitoring of 13+ appliances and regional weather data. Includes traditional appliances plus new IoT devices like car chargers, water heaters, pool pumps, and outdoor lighting.