基于arduino技术的智能农业控制系统

Narayut Putjaika, Sasimanee Phusae, Anupong Chen-Im, P. Phunchongharn, K. Akkarajitsakul
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引用次数: 62

摘要

“物联网”(IoT)是一种允许事物相互通信和连接的技术。这将改变工业和农业的模式和过程,提高效率。特别是农业是泰国经济的重要基础。因此,我们提出了一种智能农业系统(IF)来改善种植的生产过程。中频由传感器系统和控制系统两大部分组成。在本文中,我们关注的是基于传感器系统(包括温度、湿度、湿度和光强度传感器)感知到的统计数据的控制部分,即户外农场的浇水和屋顶系统。由于噪声的影响,感知到的数据并不总是准确的,因此我们应用卡尔曼滤波对数据进行平滑处理,然后将其作为决策过程的输入。在决策过程中,我们不仅考虑了遥感数据,还考虑了天气信息。生成一个决策树模型来预测天气状况。然后,基于传感数据和预测天气条件,开发一套决策规则,自动决定是否应该打开或关闭浇水和屋顶系统。此外,我们还为用户提供了通过移动应用程序手动控制浇水和屋顶系统的功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A control system in an intelligent farming by using arduino technology
“Internet of Things” (IoT) is a technology that allows things to communicate and connect with each other. This will change the patterns and processes in both industry and agriculture towards higher efficiency. Particularly, agriculture is an important foundation of Thai economy. Consequently, we propose an intelligent farming system (IF) to improve the production process in planting. IF composes of two main parts which are a sensor system and a control system. In this paper, we focus on the control part which are watering and roofing systems of an outdoor farm based on the statistical data sensed from the sensor systems (including temperature, humidity, moisture and light intensity sensors) Since the sensed data would not be always accurate due to noises, we apply Kalman filtering to smooth the data before using as an input in our decision making process. For the decision making process, we do not consider only the sensed data, but also the weather information. A decision tree model is generated to predict the weather condition. Then, a set of decision rules based on both the sensed data and the predicted weather condition is developed to automatically make a decision on whether watering and roofing system should be on or off. Moreover, we also provide functions for users to manually control the watering and roofing systems via our mobile application.
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