Abstract
"Real-time data collected from IoT sensors to detect smoke and fire events. Features include temperature, humidity, TVOC, and eCO2 levels for reliable alarm systems."
Description
Dataset Context
This dataset is crucial for developing AI-based fire alarm systems. Traditional smoke detectors can be prone to false alarms; this IoT dataset allows for multi-sensor fusion to improve accuracy.
Technical Details
- Device: Photoelectric Smoke Detector combined with IoT sensors.
- Target Variable: 'Fire Alarm' (1 = Fire, 0 = No Fire).
- Key Features:
- Temperature (C) & Humidity (%)
- TVOC (Total Volatile Organic Compounds) [ppb]
- eCO2 (CO2 equivalent) [ppm]
- Raw Sensor Data (Raw H2, Raw Ethanol)
Applications
Perfect for training Binary Classification models (Logistic Regression, Random Forest) to predict fire incidents with high precision.
Data Preview
| UTC | Temperature[C] | Humidity[%] | TVOC[ppb] | eCO2[ppm] | Fire_Alarm |
|---|---|---|---|---|---|
| 1654733331 | 20.0 | 57.36 | 0 | 400 | 0 |
| 1654733332 | 20.015 | 56.67 | 0 | 400 | 0 |
| 1654733333 | 20.029 | 55.96 | 0 | 400 | 0 |
Showing first few rows for preview
Cite This Dataset
Kaggle (2026). IoT Smoke Detection Dataset. [Dataset]. Kaggle. https://www.kaggle.com/datasets/deepcontractor/smoke-detection-dataset
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Original source: Kaggle (2026). Visit official page for more details.
Indexed by IoTDataset.com on Jan 13, 2026
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