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Multiparametric Monitoring in Equatorian Tomato Greenhouses (III): Environmental Measurement Dynamics

机译:赤道番茄大棚的多参数监测(III):环境测量动态

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摘要

World population growth currently brings unequal access to food, whereas crop yields are not increasing at a similar rate, so that future food demand could be unmet. Many recent research works address the use of optimization techniques and technological resources on precision agriculture, especially in large demand crops, including climatic variables monitoring using wireless sensor networks (WSNs). However, few studies have focused on analyzing the dynamics of the environmental measurement properties in greenhouses. In the two companion papers, we describe the design and implementation of three WSNs with different technologies and topologies further scrutinizing their comparative performance, and a detailed analysis of their energy consumption dynamics is also presented, both considering tomato greenhouses in the Andean region of Ecuador. The three WSNs use ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The present study provides a systematic and detailed analysis of the environmental measurement dynamics from multiparametric monitoring in Ecuadorian tomato greenhouses. A set of monitored variables (including CO2, air temperature, and wind direction, among others) are first analyzed in terms of their intrinsic variability and their short-term (circadian) rhythmometric behavior. Then, their cross-information is scrutinized in terms of scatter representations and mutual information analysis. Based on Bland–Altman diagrams, good quality rhythmometric models were obtained at high-rate sampling signals during four days when using moderate regularization and preprocessing filtering with 100-coefficient order. Accordingly, and especially for the adjustment of fast transition variables, it is appropriate to use high sampling rates and then to filter the signal to discriminate against false peaks and noise. In addition, for variables with similar behavior, a longer period of data acquisition is required for the adequate processing, which makes more precise the long-term modeling of the environmental signals.
机译:当前,世界人口增长带来不平等的粮食获取,而农作物的产量并未以类似的速度增长,因此未来的粮食需求可能无法得到满足。最近的许多研究工作都涉及在精准农业上使用优化技术和技术资源,特别是在大需求作物中,包括使用无线传感器网络(WSN)进行气候变量监控。但是,很少有研究集中在分析温室中环境测量特性的动态。在这两篇随附的论文中,我们描述了三种具有不同技术和拓扑结构的无线传感器网络的设计和实现,进一步详细研究了它们的比较性能,还对它们的能耗动态进行了详细分析,都考虑了厄瓜多尔安第斯地区的番茄温室。这三个WSN使用具有星形拓扑的ZigBee,具有网状拓扑的ZigBee(在此称为DigiMesh)和具有接入点拓扑的WiFi。本研究为厄瓜多尔番茄温室的多参数监测提供了环境测量动态的系统,详细的分析。首先根据其固有的可变性和它们的短期(昼夜)节律行为来分析一组监控变量(包括CO2,空气温度和风向等)。然后,根据散布表示和相互信息分析来检查它们的交叉信息。基于Bland–Altman图,在使用中等正则化和100系数阶数的预处理滤波的情况下,可以在四天内的高速率采样信号下获得高质量的节奏测量模型。因此,特别是对于快速转换变量的调整,使用高采样率然后对信号进行滤波以区别假峰值和噪声是适当的。另外,对于具有相似行为的变量,需要更长的数据采集时间才能进行适当的处​​理,这使得对环境信号的长期建模更加精确。

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