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首页> 外文期刊>International Journal of Environmental Research and Public Health >Extending Participatory Sensing to Personal Exposure Using Microscopic Land Use Regression Models
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Extending Participatory Sensing to Personal Exposure Using Microscopic Land Use Regression Models

机译：使用微观土地利用回归模型将参与感知扩展到个人接触

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摘要

Personal exposure is sensitive to the personal features and behavior of the individual, and including interpersonal variability will improve the health and quality of life evaluations. Participatory sensing assesses the spatial and temporal variability of environmental indicators and is used to quantify this interpersonal variability. Transferring the participatory sensing information to a specific study population is a basic requirement for epidemiological studies in the near future. We propose a methodology to reduce the void between participatory sensing and health research. Instantaneous microscopic land-use regression modeling (μLUR) is an innovative approach. Data science techniques extract the activity-specific and route-sensitive spatiotemporal variability from the data. A data workflow to prepare and apply μLUR models to any mobile population is presented. The μLUR technique and data workflow are illustrated with models for exposure to traffic related Black Carbon. The example μLURs are available for three micro-environments; bicycle, in-vehicle, and indoor. Instantaneous noise assessments supply instantaneous traffic information to the μLURs. The activity specific models are combined into an instantaneous personal exposure model for Black Carbon. An independent external validation reached a correlation of 0.65. The μLURs can be applied to simulated behavioral patterns of individuals in epidemiological cohorts for advanced health and policy research.
机译：个人接触对个人特征和行为敏感，包括人际间的变化将改善健康状况和生活质量评估。参与感测评估环境指标的时空变异性，并用于量化这种人际变异性。将参与感测信息转移到特定的研究人群是近期流行病学研究的基本要求。我们提出了一种方法，以减少参与式感知与健康研究之间的空隙。瞬时微观土地利用回归模型（μLUR）是一种创新方法。数据科学技术从数据中提取特定于活动且对路线敏感的时空变异性。介绍了准备和应用μLUR模型到任何移动人群的数据工作流程。 μLUR技术和数据工作流程与暴露于交通相关的黑碳的模型一起进行了说明。 μLUR示例可用于三个微环境。自行车，车载和室内。瞬时噪声评估为μLUR提供瞬时交通信息。特定于活动的模型被合并为黑碳的即时个人暴露模型。独立的外部验证得出0.65的相关性。可以将μLURs应用于流行病学队列中个体的模拟行为模式，以进行高级卫生和政策研究。

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