Smart Farming using Machine Learning
Abstract
Abstract. The traditional farming sector is undergoing a revolution with the
integration of smart technologies like machine learning and IoT. This research
paper discusses a smart farming model that enables farmers to diagnose crop
health issues by analyzing images of affected crops and relevant soil data, such
as pH and moisture. The system leverages machine learning algorithms to detect
crop diseases and provide actionable recommendations, including the type and
quantity of fertilizers, insecticides, or pesticides needed. This model promises
to enhance agricultural productivity, reduce chemical misuse, and increase
sustainability
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