A wireless sensor network framework for large-scale industrial water pollution monitoring

Yohannes Derbew, M. Libsie
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引用次数: 10

Abstract

Design and implementation of Wireless Sensor Networks (WSNs) is a challenging task because WSN research is usually application specific and each application requirement brings with it a different set of constraints and design objectives. Effective use of WSNs in large scale and long-term monitoring of industrial water pollution requires satisfying two inherently contradicting requirements particular to this domain. On the one hand, it has to be time critical in order to provide early warning during compliance violations. On the other hand, it requires long-term data collection from a large number of distributed industrial sites for trend analysis for decision-making. We present the design of a comprehensive framework for using WSNs in industrial water pollution monitoring to assist environment authorities in decision-making regarding water pollution. The suitability and effectiveness of our proposed framework is verified with an experiment using the discrete-event simulator Castalia based on the OMNeT++ simulation platform.
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面向大规模工业水污染监测的无线传感器网络框架
无线传感器网络的设计和实现是一项具有挑战性的任务,因为无线传感器网络的研究通常是特定于应用的,每种应用需求都会带来一组不同的约束和设计目标。在工业水污染的大规模和长期监测中有效地使用WSNs需要满足该领域特定的两个内在矛盾的要求。一方面,它必须是时间关键的,以便在违反法规期间提供早期预警。另一方面,它需要从大量分布的工业场地中长期收集数据,进行趋势分析,为决策提供依据。我们提出了一个综合框架的设计,用于在工业水污染监测中使用WSNs,以协助环境当局做出有关水污染的决策。利用基于omnet++仿真平台的离散事件模拟器Castalia进行了实验,验证了该框架的适用性和有效性。
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