Building air quality and pandemic risk simulation

原始论文包含对数据集特征和数据集潜在用例的高级解释。 ArchABM 可以帮助量化这些建筑和公司政策相关措施的影响。基线实验 首先研究了没有措施和减少通风的基线病例。为每种事件类型设置了时间表，以及它们的最短和最长持续时间 $\tau$ 以及重复次数。掩码不在任何地方使用 ($m_e = 0$)。会议和午餐活动被视为集体活动。场所的容量是指可以在该指定空间中出现的最大人数。建立了较低的自然通风率（$\lambda_a = 1.5$，对于通风不良的房间，$\lambda_a = 0.5$）并且没有机械通风（$\lambda_r = 0$）。与建筑相关的实验

The original paper includes a high-level explanation of the dataset's features and potential use cases. ArchABM can assist in quantifying the impacts of measures related to building and corporate policies. Baseline experiments: First, baseline scenarios with no interventions and reduced ventilation were studied. A schedule was formulated for each event type, along with their minimum and maximum durations $ au$ and the number of repetitions. Masking was not used anywhere ($m_e = 0$). Meetings and lunch events are treated as collective activities. The capacity of a venue refers to the maximum number of people that can be present in the designated space. A lower natural ventilation rate was established ($lambda_a = 1.5$, and $lambda_a = 0.5$ for poorly ventilated rooms), with no mechanical ventilation ($lambda_r = 0$). Building-related experiments

搜集汇总

背景与挑战

背景概述

该数据集基于ArchABM代理模拟器，旨在分析室内空气质量（如CO2和病毒载量），以评估建筑环境与人类互动对疫情风险的影响。它由纳瓦拉大学等机构于2021年发布，适用于时间序列研究，并遵循CC BY 4.0许可协议。