A Smart Climatic Control Strategy for Optimizing Vegetable Crop Cultivation in Greenhouse using FBANN

S. Shakya
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Abstract

Greenhouses are designed to provide the desired climatic condition for the growth of certain plants to obtain better yield. Most of the greenhouses are developed with adequate windows that allows the natural air to reach the plants to maintain the ideal temperature. The windows are usually operated manually by verifying the greenhouse temperature and the surrounding temperature. In a few cases, the manual operations are extended to control the natural light levels and the humidity inside the greenhouse. In order to improve the performances of such climatic control in a greenhouse, certain automatic systems were developed in recent years. In the proposed work, the operations are controlled using a microcontroller module and a sensor unit. The information collected from the sensors placed inside and outside the greenhouse is forwarded to a feedback gained Artificial Neural Network (FBANN) for making the desirable operation on window and light control modules. The performances of the proposed work is verified with RMSE values observed from the manually operated controller.
利用fban优化温室蔬菜作物栽培的智能气候控制策略
温室的设计是为了为某些植物的生长提供所需的气候条件,以获得更好的产量。大多数温室都有足够的窗户,让自然空气到达植物,保持理想的温度。窗户通常是通过核对温室温度和周围温度来手动操作的。在少数情况下,人工操作扩展到控制温室内的自然光水平和湿度。为了提高温室气候控制的性能,近年来开发了一些自动化系统。在所提出的工作中,使用微控制器模块和传感器单元来控制操作。从温室内外的传感器收集到的信息被转发到反馈获得的人工神经网络(FBANN),以便对窗户和灯光控制模块进行理想的操作。通过从手动操作控制器观察到的RMSE值验证了所提出工作的性能。
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