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Rules engine and complex event processor in the context of internet of things for precision agriculture

机译:规则引擎和复杂的事件处理器在精密农业的东西互联网上的背景下

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The Internet of Things (IoT) applications monitor large data flows and events in real time, some raw data is captured from devices located in wireless sensor networks (WSN) and used to make control decisions about actuators. This can be a major problem when the devices grow in number as well as the data that is captured. In this paper, we propose an architecture called "RECEP" for the dynamic processing of events generated in the context of IoT and Precision Agriculture (PA); it is made up of two components: Rules Engine (RE) and Complex Event Processor (CEP). RE allows you to configure dynamic rules conditioning input data from different sources and planning control actions on actuators, alerts, and notifications for end users or applications. The CEP component fuses the input data at the rate at which they arrive, with the rules established in the RE and it performs a prescriptive analysis that consists not only in predicting or detecting patterns of events, but in making automatic decisions. RECEP was implemented in a virtual machine with a 1.9 GHz CPU and 6 GB RAM, then it was integrated into an intelligent irrigation system of an experimental banana plot located in Machala-Ecuador. A WSN simulator was also used to generate sensor data in large quantities, the CEP was evaluated with several test cases, and results show that it consumes computational resources with a growth trend, represented by a logarithmic regression model (r-squared 0.9); that is, the more events are processed, there is a minimum consumption of resources. It was tested for fifteen days; around 25 thousand events/s were processed. Our RECEP can be implemented in low-cost infrastructure typical of small and large banana producers.
机译:物联网(IoT)应用程序实时监控大数据流和事件,一些原始数据被从位于无线传感器网络(WSN)中的设备捕获,并用于对执行器进行控制决策。当设备增长数量以及捕获的数据时,这可能是一个主要问题。在本文中,我们提出了一种称为“RECEP”的架构,用于在物联网和精密农业(PA)上生成的事件的动态处理;它由两个组件组成:规则引擎(RE)和复杂的事件处理器(CEP)。 Re允许您配置来自不同源的动态规则,并在执行器,警报和最终用户或应用程序的通知上规划控制操作。 CEP组件以他们到达的速率融合了输入数据,其中在RE中建立的规则,它执行了规定的分析,不仅包括预测或检测事件模式,而且在制定自动决策时。 RECEP是在一个带有1.9 GHz CPU和6 GB RAM的虚拟机中实现的,然后将其整合到位于马尔塔厄瓜多尔的实验香蕉情节的智能灌溉系统中。 WSN模拟器还用于产生大量的传感器数据,CEP被评估为几种测试用例,结果表明它会消耗具有由对数回归模型的增长趋势的计算资源(R范围和GT; 0.9)表示;也就是说,处理的事件越多,资源的最小消耗。它被测试了十五天;处理大约25000个活动。我们的RESEP可以在典型的小型和大型香蕉生产商典型的低成本基础设施中实施。

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