Anonymised smart meter electricity consumption data from the CKW Group distribution network in Lucerne Canton, Switzerland. 15-minute resolution, covering 2021–2024. Parquet and CSV formats. Published on Zenodo 2024. Used for large-scale household energy analytics and smart grid research.
Real IoT botnet traffic dataset from 9 commercial devices (webcams, routers, thermostats) authentically infected by Mirai and BASHLITE. Over 7M records, 115 statistical features. CSV format. Benchmark for deep-learning-based IoT anomaly and botnet detection.
Large-scale distributed IoT IDS benchmark with traffic captured at individual device interfaces across 78 heterogeneous smart city IoT devices using the Gotham testbed. PCAP and CSV. Published January 2026 on Zenodo. Designed for federated learning and decentralised IDS research.
IoT environmental sensor dataset tracking water quality and pollution risk indicators for Gaoyou Lake, China. Includes pH, dissolved oxygen, turbidity, temperature, and conductivity readings. CSV format via Kaggle. Used for aquatic pollution risk classification and IoT water monitoring research.
Longest freely available on-field IoT air quality sensor deployment: 9,358 hourly records from 5 metal oxide gas sensors in an Italian city. CSV/XLSX format. Used for gas sensor regression, drift correction, and pollution forecasting research.
Open urban sensing dataset from 130 IoT nodes across Chicago measuring temperature, humidity, pressure, light, CO, NOâ‚‚, SOâ‚‚, ozone, sound, and pedestrian/vehicle traffic. CSV via Chicago Open Data Portal. Used for smart city analytics and urban environment research.
Agricultural IoT network intrusion dataset with 1.31 million labeled flow records (532 MB) emulating a real AG-IoT farm environment. Covers crop health, weather, and soil condition data with network attack scenarios. CSV via Zenodo. Used for smart farming security research.
Real smart-home IoT dataset from non-invasive PIR motion, magnetic door/window, and temperature sensors installed in multiple households. CSV format (6.4 MB). Used for occupancy detection, activity recognition, and smart home automation research.
Large-scale IoT cybersecurity dataset with 47M+ labeled network flows from 105 real IoT devices across 33 attack types in 7 categories. PCAP and CSV formats. Built for IDS/IPS development and ML-based IoT traffic classification research.
Real-time IoT network security dataset from a live IoT infrastructure with 41 bidirectional flow features. Includes ThingSpeak-LED, Wipro-Bulb, and MQTT-Temp devices with SSH brute force, DDoS (Hping/Slowloris), and Nmap attack scenarios. CSV format. Used for adaptive IDS development.
Realistic IoT/IIoT cybersecurity dataset supporting centralized and federated learning with 15 attack types across network, application, and protocol layers. CSV and PCAP formats (~12 GB). Available via IEEE Dataport and Kaggle. Designed for edge computing IDS research.