Multi-sensor dataset for normal air, Methyl Mercaptan and Hydrogen Sulfide gas classification

The dataset includes time-series data collected by four different sensors, which measure two target gases, Hydrogen Sulfide and Methyl Mercaptan, in the presence of air. To obtain measurements, each gas was individually exposed to the multi-sensor setup while in the presence of air. The dataset is particularly useful for gas classification tasks, as deep learning and data fusion techniques can be applied to identify the target gases.

The dataset comprises time-series data collected by four sensors, which measure two target gases, Hydrogen Sulfide (H2S) and Methyl Mercaptan (CH3SH) in the presence of air. To obtain measurements, each gas was individually exposed to the multi-sensor setup, while maintaining room temperature. Table 2 in the description file presents the distribution of data samples for the target gases collected from the multi-sensor system against the true gas concentration in parts per million (ppm) at two different humidity levels. The dataset file is available in CSV format and contains 9 columns with a total of 654440x4 gas samples. The CSV file also includes additional information on temperature, humidity, and true concentrations of Hydrogen Sulfide and Methyl Mercaptan. Out of the 654440x4 samples, there are 151682x4 samples of Methyl Mercaptan, 126142x4 samples of Hydrogen Sulfide, and the remaining samples are normal air samples.

The dataset was originally published in DiVA and moved to SND in 2024.

本数据集包含由4个不同传感器采集的时间序列数据，用于检测空气环境中的两种目标气体：硫化氢（Hydrogen Sulfide）与甲硫醇（Methyl Mercaptan）。为获取测量数据，在空气环境下将单种目标气体单独通入该多传感器装置。该数据集尤其适用于气体分类任务，可结合深度学习与数据融合技术实现目标气体的识别。

本数据集包含由4个传感器采集的时间序列数据，用于检测空气环境中的两种目标气体：硫化氢（H2S）与甲硫醇（CH3SH）。为获取测量数据，将单种目标气体单独通入该多传感器装置，并保持室温环境。数据集说明文件中的表2展示了在两种不同湿度水平下，该多传感器系统采集的目标气体样本分布与以百万分比（parts per million, ppm）计量的真实气体浓度的对应关系。数据集文件采用CSV格式存储，包含9列数据，总计654440×4组气体样本。该CSV文件还额外包含温度、湿度以及硫化氢和甲硫醇的真实浓度信息。在全部654440×4组样本中，甲硫醇样本占151682×4组，硫化氢样本占126142×4组，剩余样本为纯空气样本。

本数据集最初发布于DiVA平台，并于2024年迁移至SND平台。

搜集汇总

背景与挑战

背景概述

这是一个用于气体分类的多传感器数据集，包含由四个传感器收集的时间序列数据，测量硫化氢和甲硫醇在空气中的浓度，并附带温度、湿度等环境信息。数据集总计654,440x4个样本，涵盖两种目标气体和正常空气，适用于深度学习和数据融合技术的气体识别任务，以CSV格式提供。