arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2104.04076cs.CYcs.AIcs.LG
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基于人工智能和物联网的自动灌溉系统

An artificial intelligence and Internet of things based automated irrigation system

Ömer Aydin, Cem Ali Kandemir, Umut Kiraç, Feriştah Dalkiliç

摘要:

考虑到世界上水资源的日益减少,不难看出对清洁水的需求正在增长。饮用淡水也用于灌溉,因此应计划减少淡水浪费。随着技术的发展和更便宜,更有效的解决方案的可用性,灌溉效率提高,水损失可以减少。特别是,物联网(IoT)设备已经开始在所有领域中使用。通过物联网设备和传感器,我们可以轻松、精确地收集灌溉田的温度、湿度和矿物质值。大多数关于灌溉的操作和决定都是由人来执行的。对于人们来说,在决策过程中很难拥有所有的实时数据,如温度,湿度和矿物质含量,并通过考虑它们来做出决策。人们通常根据自己的经验做出决定。在这项研究中,通过使用物联网设备和传感器获得了灌溉领域的广泛信息。从物联网设备和传感器收集的数据通过通信渠道发送并存储在MongoDB上。在Weka软件的帮助下,将数据归一化,并将归一化的数据用作学习集。作为检查的结果,选择了具有最高精度的决策树(J48)算法,并创建了人工智能模型。决策用于管理操作,如开始,维护和停止灌溉。对决策的准确性进行了评估,并根据结果对灌溉系统进行了测试。有选项来管理,远程和手动查看系统,也可以通过创建的移动应用程序查看系统的决策。

英文摘要:

It is not hard to see that the need for clean water is growing by considering the decrease of the water sources day by day in the world. Potable fresh water is also used for irrigation, so it should be planned to decrease freshwater wastage. With the development of technology and the availability of cheaper and more effective solutions, the efficiency of irrigation increased and the water loss can be reduced. In particular, Internet of things (IoT) devices has begun to be used in all areas. We can easily and precisely collect temperature, humidity and mineral values from the irrigation field with the IoT devices and sensors. Most of the operations and decisions about irrigation are carried out by people. For people, it is hard to have all the real-time data such as temperature, moisture and mineral levels in the decision-making process and make decisions by considering them. People usually make decisions with their experience. In this study, a wide range of information from the irrigation field was obtained by using IoT devices and sensors. Data collected from IoT devices and sensors sent via communication channels and stored on MongoDB. With the help of Weka software, the data was normalized and the normalized data was used as a learning set. As a result of the examinations, a decision tree (J48) algorithm with the highest accuracy was chosen and an artificial intelligence model was created. Decisions are used to manage operations such as starting, maintaining and stopping the irrigation. The accuracy of the decisions was evaluated and the irrigation system was tested with the results. There are options to manage, view the system remotely and manually and also see the system s decisions with the created mobile application.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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