Crop Disease Detection Using NLP and Deep Learning

Abstract

Nowadays, we have seen in our state, country, and others places that lot of crops are affecting from different diseases from different insects. So we have planned to develop a system for ranking of those regions which is basically infected with several diseases and which places infected more in comparisons with other regions. This work presents the first step toward a fully built, semantically enhanced decision support system for IPM. The ultimate objective is to construct a method to aid farmers in making decisions regarding the prevention of illnesses and pests as well as to create a comprehensive agriculture expertise compiled by collecting data from several different sources. With the help of NLP, sentiment analysis of the data is known, and when the farmers give text data of the symptoms as input, the disease name is generated using approaches for machine learning.