基于无线传感器网络的实时监测应用:Bajo Giuliani项目

M. Diván
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引用次数: 1

摘要

在数据驱动决策方面,实时监控日益成为一项关键资产。在金融市场、自然灾害、电信等领域,数据在合适的时机可能会产生重大影响。在本作品中,介绍了“Bajo Giuliani”项目。该项目的目的是监测“Bajo Giuliani”泻湖(阿根廷La Pampa)的水位,以支持数据驱动的决策,并避免雨季的洪水。为此目的,使用了专门用于度量和评估(M&E)项目的基于度量元数据(PAbMM)的处理体系结构。M&E项目是根据C-INCAMI(上下文信息需求、概念模型、属性、度量和指标)框架来定义的,以促进其一致性、互操作性和自动化。考虑到与区域相关的地理限制,给出了基于无线传感器网络的监测站的示意图和图示。由于数据流在容量上不受限制,并且持久数据可能是建模历史行为所必需的,因此提出了一种使用与被监视实体相关的摘要的综合策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying the Real-Time Monitoring based on Wireless Sensor Networks: The Bajo Giuliani Project
In terms of the data-driven decision making the real-time monitoring becomes day by day in a key asset. The financial markets, natural disasters, telecommunications among other are scenarios in which the data in the right moment could make a big difference. In this work, the “Bajo Giuliani” project is introduced. The project’s aim is related to the monitoring of the water level in the “Bajo Giuliani” lagoon (La Pampa, Argentina) for supporting the data-driven decision making and avoiding the floods in the rain season. With this purpose, the Processing Architecture based on Measurement Metadata (PAbMM) which is specialized in the Measurement and Evaluation (M&E) projects is used. The M&E projects are defined in terms of the C-INCAMI (Context-Information Need, Concept Model, Attribute, Metric, and Indicator) framework for fostering its consistency, interoperability, and automatization. The monitoring stations based on Wireless Sensor Networks are schematized and shown considering the geographic limitations related to the zone. Because the data stream is not limited in volume, and the persistent data could be necessaries for modeling the historical behavior, a synthesis strategy is proposed using the synopsis related to the entity under monitoring.
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