An Intelligent Crop Advisory Framework for Precision Agriculture Using Machine Learning Techniques
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Abstract
Agriculture is still the main way of earning a living for many people in developing countries like India. But small and poor farmers often struggle with choosing the right crops, dealing with poor soil nutrients, and managing plant diseases. These problems greatly affect how much they can grow and how much money they make. This research introduces a Smart Crop Advisory System that uses Machine Learning and Deep Learning to give smart advice to farmers. The system has three main parts: it suggests which crops to grow based on the soil and weather, recommends the right fertilizers based on soil type and crop needs, and detects plant diseases by analysing leaf images. The system combines smart models with a web platform so farmers can easily access the advice. The test results show that this system helps farmers make better decisions and grow more crops. This approach shows how artificial intelligence can help make farming more precise and sustainable
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