基于物联网的樱桃番茄大棚温湿度模糊监测

A. Yumang, Lemuel Aldwin P. Garcia, Gerome A. Mandapat
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引用次数: 3

摘要

温度和湿度是两个严重影响植物生长的环境因素。在传统农业中,外部环境条件的不可预测性给获得稳定的水果产量带来困难。这可以避免在封闭的环境中,通过一个自动化的温度和湿度控制器的实施。本文所进行的研究显示了温室环境中保持温度和湿度水平对樱桃番茄果实产量的影响。内部温度和湿度水平的变化是通过传感器和控制设备来完成的,这些设备负责影响内部读数,使其保持在一定的阈值内。在决策过程中,模糊逻辑的实施自动化了维持温室内最佳条件所需的行动。为了确定受控温室温度和湿度水平是否对樱桃番茄产量产生积极影响,记录了室外地块和温室地块的收成,并使用双样本t检验进行了统计处理。在零假设下,水果产量没有增加的假设,而在备用假设下,水果产量增加的假设。计算值t = 1.7271,临界值为1.701,使用28自由度和95%的置信区间,接受备用假设。因此,表明模糊逻辑控制器有效地做出适当的决策,以保持水果生产的最佳温度和湿度水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IoT-based Monitoring of Temperature and Humidity with Fuzzy Control in Cherry Tomato Greenhouses
Temperature and Humidity are two environmental factors that heavily impact the growth of a plant. The unpredictability of external environmental conditions in traditional farming present difficulties in obtaining stable fruit yields. This can be avoided in enclosed environments through the implementation of an automated temperature and humidity controller. The study performed in this paper shows the effect of maintaining temperature and humidity levels within a greenhouse environment on cherry tomato fruit yield. Changes to internal temperature and humidity levels were done through sensors and controlling devices responsible for influencing internal readings to remain within a certain threshold. The implementation of fuzzy logic in the decision making automated the actions required to maintain optimal conditions within the greenhouse. To determine whether the controlled greenhouse temperature and humidity levels introduced a positive effect on cherry tomato yield, harvests from an outside plot and the greenhouse plot were recorded and compared using the two-sample t-test statistical treatment. Under the null hypothesis, the assumption that no increase in fruit yield was made, whereas the assumption that an increase in fruit yield was made under the alternate hypothesis. With a calculated value of t = 1.7271 and a critical value of 1.701 which was found using a degree of freedom of 28 and a confidence interval of 95%, the alternate hypothesis was been accepted. Thus, showing that the fuzzy logic controller has been effective in making the appropriate decisions to maintain optimal temperature and humidity levels for fruit production.
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