A Smart Hydroponic Farming System Using Machine Learning

L. Kondaka, R. Iyer, Shreyas Jaiswal, Altaf Ali
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Abstract

The growing demand for food in the world may not be met with the traditional farming system coupled with rising pollution level and oscillations in climate. Hydroponic System is a system of growing crops without soil, produces organic crops without using fertilizers or pesticides and its results are better than traditional farming based on yield and quality. Hydroponic System enables farming of crops in indoors at convenience and requires negligible attention of user. It increases the productivity and reduces the water utilization up to 80-90% as compared to the traditional farming system. We propose a Smart Hydroponic Farming System to grow various crops by maintaining and controlling environmental parameters such as temperature, water flow or level, nutrients in water, duration of lights, etc. using Machine learning model. After selecting the plant, the Raspberry Pi will automatically set the environment for that plant as trained in ML model and the growing process will begin automatically. User will be able to monitor and control the system by making use of Web Portal.
利用机器学习的智能水培农业系统
传统的农业系统可能无法满足世界上不断增长的粮食需求,再加上污染水平的上升和气候的波动。水培系统是一种无土栽培作物的系统,生产的有机作物不使用化肥或农药,其结果优于传统农业的产量和质量。水培系统可以方便地在室内种植作物,无需用户注意。与传统农业系统相比,它提高了生产力,并将水的利用率降低了80-90%。我们提出了一种智能水培农业系统,通过使用机器学习模型来维持和控制环境参数,如温度、水流或水位、水中营养物质、光照时间等,来种植各种作物。在选择植物后,树莓派将自动为该植物设置ML模型训练的环境,并且生长过程将自动开始。用户可以利用Web Portal对系统进行监视和控制。
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