基于Boltuino平台的气候适应性认知灌溉系统,实现高效用水

Ashim Mondal, P. Dutta
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引用次数: 1

摘要

农作物生产也许是当今世界上最具挑战性的活动之一。传统耕作方式的缺点主要是灌溉用水过多,浪费时间和资金,依赖不可再生能源和对人力的要求。为了确保国家的进步,至关重要的是要以战略方式发展农业部门。这项工作的目的是设计一个基于物联网的认知系统,对节水有实质性的影响。农民可以通过互联网或他们的移动设备获取土壤湿度、温度和湿度的信息,灌溉电机将根据这些数据自动开关。能够在舒适的家中控制他们的灌溉系统将在许多方面对农民极为有益。农民的时间和劳动将被节省,农民将在夏季和冬季躲避炎热和寒冷。此外,该系统还具有对降雨的响应能力。根据降雨数据,泵继电器将打开和关闭,以确保节能。BOLT模块已被用于收集各种参数和警报系统的实时数据。使用Arduino Uno和BOLT,为该项目创造了“Boltuino”的绰号。在这里,提议的策略是通过室内农业设置来实现的。收集的数据表明节水效果显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boltuino Platform Based Cognitive Irrigation System with Weather Adaptability for Efficient Water Use
Crop production is perhaps one of the most challenging activities that one may undertake in today's world. Among the disadvantages of traditional farming methods main are the excessive water use during irrigation, the waste of time and capital, the reliance on nonrenewable energy sources and the requirement for human labor. To ensure the progress of the country, it is crucial that the agricultural sector is developed in a strategic manner. The purpose of this work is to design an Internet of Things-based cognitive system that has a substantial impact on water conservation. It is possible for farmers to access information on soil moisture, temperature, and humidity via the internet or their mobile devices, and the irrigation motor will automatically switched on and off in response to this data. Being able to control their irrigation systems from the comfort of their homes will be extremely beneficial to farmers in many ways. Farmer's time and labor will be saved, and the farmer will be sheltered from the heat and cold in both the summer and winter seasons. In addition, the proposed system has the capability to response towards the rain. On the basis of the rain data, the pump relay will be ON and OFF to ensure energy saving. The BOLT module has been used to collect real-time data on a variety of parameters as well as alert systems. Using the Arduino Uno and BOLT, the moniker “Boltuino” was coined for the project. Here, the proposed strategy is realised by means of an indoor farming setup. The collected data indicates significant water savings.
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