Abstract
"Simulated smart city environment capturing multimodal data from distributed urban sensors and surveillance sources. Includes synchronized environmental and visual data for edge computing and urban anomaly detection research."
Description
Dataset Overview
UrbanIoT-Anomaly simulates a realistic smart city environment by capturing multimodal sensor data and video surveillance footage from multiple urban locations.
Data Components
- Environmental Sensors: Temperature, humidity, gas levels, vibration, noise, motion
- Surveillance Data: Video feeds capturing human activity and crowd density
- Time Series: Synchronized readings from distributed sensor network
- Labels: Normal vs Anomalous instances
Key Features
Multi-source data fusion, real-time anomaly detection, crowd monitoring, IoT sensor network analysis, edge computing applications.
Data Preview
| Timestamp | Location_ID | Temperature_C | Humidity_% | CO2_ppm | Crowd_Density | Anomaly_Label |
|---|---|---|---|---|---|---|
| 2024-12-01 10:00 | Urban_1 | 22.5 | 65 | 650 | 0.35 | Normal |
| 2024-12-01 10:15 | Urban_1 | 22.8 | 68 | 720 | 0.85 | Anomaly |
| 2024-12-01 10:30 | Urban_2 | 21.2 | 72 | 580 | 0.12 | Normal |
Showing first few rows for preview
Cite This Dataset
Kaggle (2026). UrbanIoT-Anomaly: Multimodal Smart City Dataset. [Dataset]. Kaggle. https://www.kaggle.com/datasets/ziya07/urbaniot-anomaly-multimodal-smart-city-dataset
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Original source: Kaggle (2026). Visit official page for more details.
Indexed by IoTDataset.com on Jan 12, 2026
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