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Systems approach to evaluating sensor characteristics for real-time monitoring of high-risk indoor contaminant releases

机译：评估传感器特性的系统方法，用于实时监测高风险室内污染物的释放

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Rapid detection of toxic agents in the indoor environment is essential for protecting building occupants from accidental or intentional releases. While there is much research dedicated to designing sensors to detect airborne toxic contaminants, little research has addressed how to incorporate such sensors into a monitoring system designed to protect building occupants. To design sensor systems, one must quantify design tradeoffs, such as response time and accuracy, and select values to optimize the performance of an overall system. We illustrate the importance of a systems approach for properly evaluating such tradeoffs, using data from tracer gas experiments conducted in a three-floor building at the Dugway Proving Grounds, Utah. We explore how well a Bayesian interpretation approach can characterize an indoor release using threshold sensor data. We use this approach to assess the effects of various sensor characteristics, such as response time, threshold level, and accuracy, on overall system performance. The system performance is evaluated in terms of the time needed to characterize the release (location, amount released, and duration). We demonstrate that a systems perspective enables selecting sensor characteristics that optimize the system as a whole. (c) 2006 Elsevier Ltd. All rights reserved.
机译：在室内环境中快速检测有毒物质对于保护建筑居民免受意外或故意释放至关重要。尽管有很多研究致力于设计用于检测空气中有毒污染物的传感器，但很少有研究涉及如何将此类传感器并入旨在保护建筑居民的监测系统中。要设计传感器系统，必须量化设计权衡，例如响应时间和准确性，并选择值以优化整个系统的性能。我们使用在犹他州Dugway试验场的三层建筑中进行的示踪气体实验数据，说明了正确评估此类权衡的系统方法的重要性。我们探索了使用阈值传感器数据的贝叶斯解释方法可以如何很好地表征室内释放。我们使用这种方法来评估各种传感器特性（例如响应时间，阈值水平和准确性）对整体系统性能的影响。根据表征释放所需的时间（位置，释放量和持续时间）来评估系统性能。我们证明，从系统角度出发，可以选择可以优化整个系统的传感器特性。 （c）2006 Elsevier Ltd.保留所有权利。

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