利用物联网远程监控基于Web的作物产量预测智能水培系统

V. Mamatha, J. Kavitha
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引用次数: 0

摘要

肥料、农药、农用化学品、小块分散的土地以及其他问题困扰着印度等发展中国家的农业。消费者还要求高质量、不含农药和农药的健康饮食。采用水培系统可以满足上述困难和要求,水培系统可以是有机的。如果控制和监测得当,这种农业可以获得高产量。提出了一种基于web应用的智能农业系统,通过适当的物联网平台和必要的传感器网络相结合,实现远程监控。该系统控制植物水培生长的必要条件,种植者可以使用物联网远程控制农业。现场部署了各种传感器来收集温度、湿度、pH值和含水量等参数。收集到的传感器数据和外部输入数据,如地区名称、作物名称、面积(英亩)和水培系统类型,然后被发送到微控制器,微控制器依次处理数据,然后对其采取行动。收集到的数据被发送到云端,进行处理,并将通知发送给农民。这个提议的web应用程序根据给定的传感器和用户输入,为农民提供农作物产量的估计。作物产量预测以色调提供,并使用随机森林算法进行估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remotely monitored Web based Smart Hydroponics System for Crop Yield Prediction using IoT
Manures, pesticides, agricultural chemicals, small and fragmented land holdings, and other problems plague agriculture in developing nations like India. Consumers is also demanding a healthier diet that is high in quality and free of agricultural chemicals and pesticides. The above mentioned difficulties and demands are met by using the system of hydroponics, which can be organic. This kind of agriculture could result in a high yield if properly controlled and monitored. A smart agriculture system based on web application is proposed for remote monitoring by combining an appropriate IoT platform with the necessary sensor network. The proposed system controls the necessary conditions for the plant to grow hydroponically, and cultivators can remotely control agriculture using IoT. Various sensors are deployed in the field to collect parameters such as temperature, humidity, pH and water content. The sensor data that has been collected and the external input data such as the District Name, Crop Name, Area in acres and the Type of Hydroponics system is then sent to microcontroller, which in turn processes the data and then acts on it. The data that has been collected is sent to the cloud, processed and the notifications are delivered to the farmers. The proposed web application provides the farmers with an estimate of how much crop yield will be produced based on the given sensor and user input. The crop yield prediction is provided in tones and is estimated using Random Forest algorithm.
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