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Plume Source Detection Using a Process Query System

机译:使用过程查询系统检测烟源

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摘要

A Process Query System (PQS) has the capability of filtering large volumes of real time data originating from a field of networked Physical Sensors. Modern air quality monitoring techniques such as Fourier Transform Infra-Red (FTIR) spectroscopy will eventually provide massively distributed real time contamination data at high fidelity. As large networks of these sensors are deployed, improved techniques of data retrieval and assimilation will be required. The case of detecting a diffusion event such as a hazardous chemical plume is considered. In this scenario, a plume model based on an Ensemble Kalman Filter (EnKF)is submitted to the PQS which manages multiple hypotheses explaining the current observations. The feasibility of such an application is demonstrated and results from preliminary simulations are presented.
机译:流程查询系统(PQS)具有过滤来自联网物理传感器领域的大量实时数据的功能。诸如傅立叶变换红外(FTIR)光谱之类的现代空气质量监测技术最终将以高保真度提供大量分布的实时污染数据。随着这些传感器的大型网络的部署,将需要改进的数据检索和同化技术。考虑检测到诸如危险的化学羽流等扩散事件的情况。在这种情况下,基于Ensemble Kalman滤波器(EnKF)的羽状模型将提交给PQS,该模型管理解释当前观测值的多个假设。演示了这种应用程序的可行性,并提供了初步仿真的结果。

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