Analysis of the Agricultural Data Using Machine Learning Techniques
DOI:
https://doi.org/10.61841/c2hfbe46Keywords:
Agriculture, Farming, ICT, KNNAbstract
Information Communication and Technology (ICT) is one of the widely used areas, which, when used along with farming, is often known as E-Agriculture. It is one of the most prominent applications that is being established as well as used as a revolutionary solution to utilize ICT within the countryside. A broad range of remedies for some farming obstacles is offered by information engineering. Though constant cropping modifications, dirt physiochemical details, enzymes, as well as various microorganisms that cause replant issues are some of the main features that need to be known for proper farming, understanding basic ground-related issues, as well as the amount of liquid content in the soil, are definitely some of the major components of farming. In order to find a solution for proper farming, in this paper, we have proposed a single operating system that, in turn, helps you to evaluate the details of the cultivatable soil together with the assistance of receptors and data mining tactics. Machine learning techniques like K Nearest Neighbor (KNN) will give perfect assistance to the farmers, as the network would provide a better solution for what kind of crops need to be grown and what the expected additional features are required for getting the best crop at the given land. This would benefit the farmer to a greater extent, as it would let them grow the crop that best suits the land.
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