SmartFarm: A Machine Learning-Based Analytical System for Soil Classification and Crop Recommendation in Precision Agriculture

Abstract

Abstract: SmartFarm is an innovative machine learning-driven analytical system designed to revolutionize precision agriculture through accurate soil classification and tailored crop recommendations. The project focuses on collecting comprehensive soil and historical crop data, employing rigorous preprocessing techniques, and implementing knowledge-based classification and non-parametric classifiers such as decision trees and neural networks. The system integrates these models, ensuring a cohesive approach to support seamless decision-making for farmers. With a user-friendly interface, SmartFarm enables farmers to input soil data and receive personalized crop recommendations. The project's scalability, adaptability, and commitment to iterative improvement through user feedback make it a promising solution for enhancing agricultural productivity and sustainability. The outcomes contribute to the evolving landscape of precision agriculture, emphasizing the power of machine learning in informed decision support systems. The outcomes underscore the potential of machine learning in fostering informed decision-making and sustainable farming in the evolving landscape of precision agriculture