Paper Contents
Abstract
Machine Learning, the innovative powerhouseof technology, has ushered in a new era of possibilities. Frompersonalized recommendations to predicting outcomes,machine learning is the driving force behind countlessadvancements, promising a future where computers not onlyunderstand but also learn from the data they encounter. Overthe last two decades, India has witnessed a substantial declinein the performance of a majority of its crops, attributed to theimpacts of climate change. To empower policymakers andfarmers with valuable insights for effective marketing andstorage decisions, it becomes imperative to anticipateagricultural yield before the actual harvest. This initiative aimsto aid farmers in making well-informed choices regarding cropselection and estimating yields before cultivation. The projectintroduces an interactive prediction system designed to addressthis challenge, providing farmers with accessible outcomesthrough an online graphical user interface. The predictivecapabilities of this system leverage data analytics inagricultural forecasting, utilizing various techniques andalgorithms. Our recommendation algorithm takes into accountmultiple parameters, including temperature, humidity, rainfall,and pH levels, as well as nutrient components like nitrogen(N), phosphorus (P), potassium (K), and moisture content. Theapplication of data mining, a process involving the analysis ofdata from diverse perspectives to distill meaningfulinformation, allows for the determination of crop yield growth.The project notably utilizes well-established and highlyefficient supervised machine learning algorithms. Given thateach state in India possesses a distinct soil compositionnecessitating varied analytical approaches, the primaryobjective of this initiative is to recommend optimal cropchoices tailored to specific soil types. Additionally, the projectendeavors to augment crop yield during harvesting, therebyoffering substantial benefits to farmers. Through this holisticstrategy, the project aspires to transform agriculturaldecision-making by furnishing farmers with cutting-edge toolscapable of bolstering productivity and addressing challengesarising from climate-induced factors.
Copyright
Copyright © 2024 Srivasthan V A. This is an open access article distributed under the Creative Commons Attribution License.
