Synthetic Smart Home IoT Sensor Dataset — Tropical Climate
Free CC0 synthetic dataset: 10,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Tropical Climate, 22°C.
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Free CC0 synthetic dataset: 10,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Tropical Climate, 22°C.
View DatasetFree CC0 synthetic dataset: 10,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Cold Climate, 22°C.
View DatasetFree CC0 synthetic dataset: 10,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 16% Attacks. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 1,000 rows of vehicle speed, engine RPM, fuel level and driving-event labels. Sedan+SUV+Truck. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 10,000 rows of Modbus, OPC UA and DNP3 flows labelled for SCADA intrusion detection. 15% Attacks. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 1,000 rows of heart rate, blood pressure, SpO2, body temperature and glucose vitals. 3 Age Groups, 7 Patients.
View DatasetFree CC0 synthetic dataset: 500 rows of labelled network flows covering DoS, DDoS, botnet and reconnaissance traffic. 18% Attacks.
View DatasetFree CC0 synthetic dataset: 2,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Arid Climate, 21°C. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 100 rows of indoor temperature, humidity, CO2, light and occupancy readings. 26.5°C. Reproducible from its seed.
View DatasetFree CC0 synthetic dataset: 1,000 rows of indoor temperature, humidity, CO2, light and occupancy readings. Reproducible from its seed.
View DatasetReproducible large-scale IoT network dataset from 78 emulated devices using MQTT, CoAP, and RTSP protocols. Includes benign and malicious traffic with DoS, brute force, scanning, and C&C attacks in PCAP and CSV formats.
View DatasetComprehensive smart home dataset with 1,048,575 rows and 31 columns including timestamps, device states (TV, oven, lights, fridge) and activity labels for machine learning classification of daily activities.
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