Modelling threshold exceedence levels for spatial stochastic processes observed by sensor networks

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) Pub Date : 2014-04-21 DOI:10.1109/ISSNIP.2014.6827635

G. Peters, Ido Nevat, Shaowei Lin, Tomoko Matsui

引用次数: 2

Abstract

We develop a new framework for explicitly modelling the threshold exceedence levels of the spatial stochastic process being monitored by a sensor network. Our framework also allows incorporating additional observed features as explanatory factors for the behaviour of the spatial stochastic process, and in particular the probability of exceedence of a user defined threshold level in any given region of space. Such a model has many practical applications for accurate decision making under uncertainty when the monitored process exceeds user specified critical thresholds.

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由传感器网络观测的空间随机过程的阈值超越水平建模

我们开发了一个新的框架，用于明确地模拟由传感器网络监测的空间随机过程的阈值超越水平。我们的框架还允许将额外观察到的特征作为空间随机过程行为的解释因素，特别是在任何给定的空间区域中超过用户定义的阈值水平的概率。这种模型在不确定情况下，当被监测的过程超过用户指定的临界阈值时，具有精确决策的许多实际应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

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