Volume - 3 | Issue - 3 | september 2021
DOI
10.36548/jitdw.2021.3.002
Published
25 October, 2021
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.
KeywordsGreenhouse optimization climatic control back-propagation ANN crop yield improvement
