基于物联网的可编程控制器智能灌溉系统的开发

Ivony Hari, Elita Rahmarestya, H. Harsono
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引用次数: 0

摘要

智能灌溉系统是一种基于物联网(IoT)的传感器、自动化和控制技术的农业用地自动灌溉和监测系统。该系统可以将以前手工执行的农业活动减少到减少人工监督的自动系统中。广泛开发的智能灌溉系统使用Arduino作为控制器。Arduino仍然缺乏响应,耐久性低,对温度变化敏感,因此需要经常维护以避免天气干扰,昆虫等。本文介绍了一种以可编程控制器(PLC)为控制器,土壤湿度传感器为湿度测量工具的智能灌溉系统的开发。使用PLC作为控制器的优点是更稳定,具有更高精度的传感器兼容性。因此,结果更加一致和准确。PLC系统是可扩展的,允许包含更多的通道传感器和其他测量仪器。开发的系统可以收集土壤湿度条件的数据,触发阀,并使用洒水装置进行自动灌溉,减少甚至消除了人工干预的需要。物联网从传感器收集数据,并将数据更新到数据库系统,允许用户实时监控土地状况。与传统方法相比,开发的系统预计可节省人力(20%)和用水量(42.47%)。关键词:智能灌溉;物联网;PLC;湿度传感器;喷水灭火系统
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of IoT Based Smart Irrigation System with Programmable Logic Controller
Smart irrigation system is an automatic irrigation and monitoring system on agricultural land with a sensor, automation, and control technology based on the Internet of Things (IoT). This system can reduce the agricultural activities that were previously performed manually into an automatic system with a reduced human supervision. Smart Irrigation systems that are widely developed used Arduino as the controller. Arduino still lacks in response, low durability, and sensitivity to temperature change, hence requiring frequent maintenance to avoid weather disturbances, insects, and others. This paper presents a development of a smart irrigation system using a Programmable Logic Controller (PLC) as the controller and a soil moisture sensor as a humidity condition measurement tool. The advantage of using PLC as a controller is more stable and has sensor compatibility with higher accuracy. Hence the results are more consistent and accurate. The PLC system is expandable, allowing for the inclusion of more channels for sensors and other measurement instruments. The developed system can collect data on soil moisture conditions, trigger valves, and perform auto irrigation using sprinklers, reducing or even eliminating the need for human intervention. The IoT collects data from sensors and updates the data into a database system, allowing users to monitor the land conditions in real-time. The developed system was predicted to save manpower (20%) and water usage (42.47%) compared to the conventional method. Keywords : Smart Irrigation; IoT; PLC; Moisture Sensor; Sprinkler
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