Published on 16 September 2024

Indoor Fire Dataset of Multi Sensor Data (Small Scale Test Chamber)

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V, Pascal

Description

The dataset contains 4 incipient fire scenarios (wood, candles, cable, lunts; indicated by the column "scenario_label") carried out in a (2 x 0.8 x 0.6)m^3 test chamber without ventilation. Each scenario was repeated 4-6 times (indicated by he column "number_label") in random order with background sequences in between to reduce the influence of prehistory. Each experiment consists of multiple stages (up to 6 stages, indicated by the column "intensity_label") to simulate the development phase of a real scale fire in the small scale setup. The wood, cable and lunt material was burned using a 12 A heating coil, the candles fire was ignited with a lighter. The dataset consists of 2900 rows and 18 columns and is structures as a continuous multivariate time series. Each row represents the sensor measurements (CO2, CO, H2, humidity, particulate matter of different sizes, air temperature, VOC and UV) from one of four unique sensor nodes placed in the test chamber at a specific timestamp. In addition, a trend value based on the Kendall-Tau coefficient was calculated for each sensor measurement. The "Sensor_ID" column can be utilized to access data from different sensor node positions.

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Mentions (0)

Metrics

Dataset Index

1.6

FAIR Score

65%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley Data

Assigned Domain

Subfield

Safety, Risk, Reliability and Quality

Field

Engineering

Domain

Physical Sciences

Confidence Score

40%

Source

Scholar Data Model

Keywords

Data MiningMachine LearningTime SeriesApplication of SensorsFire DetectionTransfer Learning

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00