在没有传感器数据的情况下,以知识为基础生成可信的空气质量地图

Duarte Vital, Pedro Mariano, S. Almeida, Pedro Santana
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引用次数: 0

摘要

工业化增加了空气污染源,这是造成重大健康问题的一个原因。因此,空气污染成为一个日益关注的问题,有必要监测和方便地可视化空气污染数据。全世界有成千上万的空气质量监测站用来测量空气质量。此外,已经开发了许多应用程序来可视化空气污染,这些应用程序使用这些空气质量监测站收集的信息以及其他信息来源,如交通强度或天气预报。本文介绍了一种新的图形工具,它利用了一种新的信息来源:空气污染源的专家知识。该工具允许专家表示空气污染源及其动态,并将它们分配到不同的地图元素。作者对30名参与者进行了工具的可用性和可行性测试,其中6名是环境专家。得到的结果和提供的反馈表明,所提出的方法是对基于传感器的映射方法的有希望的补充。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge-Based Generation of Plausible Air Quality Maps in the Absence of Sensor Data
Industrialization increased air pollution sources, which is a cause of major health problems. As such, air pollution became a growing concern and there is a need to monitor and easily visualize air pollution data. There are thousands of air quality monitoring stations throughout the world that are used to measure air quality. Moreover, there are plenty of applications that have been developed to visualize air pollution that use information gathered by these air quality monitoring stations as well as other sources of information, such as traffic intensity or weather forecasts. This paper introduces a novel graphical tool that taps on a new source of information: expert knowledge of air pollution sources. This tool allows experts to represent air pollution sources and their dynamics, and to assign them to different map elements. The authors have performed tool's usability and viability tests with 30 participants of which 6 are environmental experts. The obtained results and the provided feedback show that the proposed approach is a promising complement to sensor-based mapping approaches.
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