Paper Contents
Abstract
Horticulture heavily depends on soil. Different types of soil exist. Different components can be found in different types of soil, and different types of harvests can grow on different types of soil. To compare whether crops perform better in particular soil types, we need to know the components and characteristics of various soil types. AI tactics may be helpful in this circumstance. In the study of horticulture information, artificial intelligence is still a developing and experimental topic. We have suggested a model that forecasts the appropriate crops that will successfully harvest in a given soil scenario. We are using a few deep learning algorithms to perform a few AI computations, which provides us with the best accuracy and prediction outcomes in the shortest amount of time.. The primary goal of this project is to recommend the most effective crop that should be grown in the provided soil input image. We employed a number of deep learning techniques for this scenario, including CNN (Convolutional Neural Networks), which is mostly used for object detection and image classification. A model should be trained and tested using CNN while receiving input in the form of fresh images. The model will categorise the different types of soil and recommend the best plants to grow there.
Copyright
Copyright © 2023 V. Ch. Karthikeya Sarma. This is an open access article distributed under the Creative Commons Attribution License.
