Crop Recommendation Assistant Using Machine Learning

Abstract

Agriculture has a vital role in India's economy. The most common issue that Indian farmers face is that they are not able to choose the right crop for their soil. Because of this approach, the likelihood of soil degradation is reduced, and crop health is improved. Precision agriculture has the potential to solve the farmers' predicament. A soil database acquired from the farm characterizes exact agriculture. The information gathered by these sensors is stored in the microcontroller and analyzed by using machine learning techniques such as random forest to produce crop growth recommendations. This project emphasizes engaging a convolutional neural network as a primary method for deciding whether a plant is at risk of disease [1].