基于距离的分布式多传感器节点室内实验室早期火灾指标分析

IF 3 3区 农林科学 Q2 ECOLOGY
Pascal Vorwerk, J. Kelleter, Steffen Müller, Ulrich Krause
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引用次数: 0

摘要

这项工作分析了一个新的室内实验室数据集,该数据集着眼于代表不同初始火灾场景的受控和现实实验中的早期火灾指标。实验是在室内实验室环境的约束下进行的,在不同的房间位置使用多个分布式传感器节点。每个传感器节点收集颗粒物(PM)、挥发性有机化合物(VOCs)、一氧化碳(CO)、二氧化碳(CO2)、氢气(H2)、紫外线辐射(UV)、空气温度和湿度的多变量时间序列数据。这些数据对机器学习和数据科学界的研究人员来说具有巨大价值,他们热衷于探索创新和先进的统计和机器学习技术。它们是开发早期火灾探测系统的宝贵资源。根据火源和传感器节点之间的曼哈顿距离对收集的数据进行分析。我们发现,特别是较大的颗粒物(>0.5μm)和挥发性有机物显示出与强度的显著相关性,作为到源的曼哈顿距离的函数。此外,我们观察到挥发性有机物、PM和CO的传播行为存在差异,由于存在链传播效应,这些差异在初期火灾场景中尤其相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distance-Based Analysis of Early Fire Indicators on a New Indoor Laboratory Dataset with Distributed Multi-Sensor Nodes
This work analyzes a new indoor laboratory dataset looking at early fire indicators in controlled and realistic experiments representing different incipient fire scenarios. The experiments were performed within the constraints of an indoor laboratory setting using multiple distributed sensor nodes in different room positions. Each sensor node collected data of particulate matter (PM), volatile organic compounds (VOCs), carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2), ultraviolet radiation (UV), air temperature, and humidity in terms of a multivariate time series. These data hold immense value for researchers within the machine learning and data science communities who are keen to explore innovative and advanced statistical and machine learning techniques. They serve as a valuable resource for the development of early fire detection systems. The analysis of the collected data was carried out depending on the Manhattan distance between the fire source and the sensor node. We found that especially larger particles (>0.5 μm) and VOCs show a significant dependency with respect to the intensity as a function of the Manhattan distance to the source. Moreover, we observed differences in the propagation behavior of VOCs, PM, and CO, which are particularly relevant in incipient fire scenarios due to the presence of strand propagation effects.
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来源期刊
Fire-Switzerland
Fire-Switzerland Multiple-
CiteScore
3.10
自引率
15.60%
发文量
182
审稿时长
11 weeks
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