Analysis of the Agricultural Data Using Machine Learning Techniques

Information Communication and Technology (ICT) is one of the widely used area which when used along with farming is often known as E-Agriculture. It is one of the most prominent application 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 various microorganisms that causes replant issues are some of the main features that needs to be known for proper farming, understanding of basic ground related, 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 of proper farming, in this paper, we have proposed a single operating system which 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 Neighbour(KNN) will give an perfect assistance to the farmers, as the network would provide a better solution of what kind of crops needs to be grown and what is the expected additional features 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.