Parametric Estimation and Optimization of Automatic Drip Irrigation Control System using Fuzzy Logic

Sikandar Ali
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Abstract

Food security is a serious problem for every developed or underdeveloped country and water is a key component of it. This is the modern era of technology but unfortunately, even today we are still using traditional methods for irrigation. Agriculture uses almost 80% to 85% of drinkable water for cultivation purposes. The ratio of water consumption will continue to rise as the world population is increasing. To meet up those demands and efficiently use the resources drip irrigation has been proposed in this research work, which irrigates directly to the roots of plants and safe water from getting wasted in the watercourse. To control irrigation, a fuzzy logic-based system has been developed. The proposed system monitors agricultural parameters like temperature, level of nutrients, and soil moisture to control irrigation. The system continuously monitors the agricultural parameters and controls the water pump accordingly. The simulation has been done using MATLAB which is based on fuzzy rules. The usage of such an automatic system can not only save water but also reduces workforce, power consumption, etc. It also increases productivity as it can provide the exact amount of water and nutrient directly to the plants.
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基于模糊逻辑的自动滴灌控制系统参数估计与优化
粮食安全是每个发达国家或欠发达国家面临的一个严重问题,而水是其中的一个关键组成部分。这是现代科技的时代,但不幸的是,即使在今天,我们仍在使用传统的灌溉方法。农业将80%到85%的饮用水用于种植。随着世界人口的增长,用水量的比例将继续上升。为了满足这些需求,有效地利用资源,本研究提出了滴灌技术,直接灌溉植物的根部,保证水不被浪费在水道中。为了控制灌溉,开发了一个基于模糊逻辑的系统。该系统监测农业参数,如温度、营养水平和土壤湿度,以控制灌溉。系统对农业参数进行连续监测,并对水泵进行相应的控制。采用基于模糊规则的MATLAB软件进行了仿真。使用这种自动化系统不仅可以节约用水,还可以减少劳动力,电力消耗等。它还可以提高生产力,因为它可以直接为植物提供准确数量的水和营养。
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