An Intelligent Crop Recommendation System using Deep Learning
Keywords:
Crop yield, Neural Network, Image processing, Remote sensing, K-Nearest Neighbor methodAbstract
A promising study area has been in the work of prediction of crop production based on certain factors like soil, characteristics of crop, water, etc. Agriculture elements like as weather, rain, the fertilizer used, pesticides, and the type of soil are some of the primary contributors to increased crop production. The presence of certain nutrients like Phosphorus, Nitrogen, Magnesium, Sulfur including some others are investigated in this research using a hybrid approach of Neural network and Image Processing to investigate soil supplements. The purpose of this research is to examine the approaches employed in extracting the water bodies utilizing the mode of satellite remote sensing. The goal of the proposed work is to collect the data of temperature and humidity and utilize algorithm of clustering with the method of k-Nearest Neighbor to find out the patterns which are all hidden in them with a help of huge amount of dataset. By this way the retrieved data is converted into data which can be used in the climate prediction and categorization.
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