Disease Detection of a Plant Leaf using Image Processing and CNN with Preventive Measures

Abstract

One of the biggest factors that increases agricultural productivity is the economic climate. Due to the aforesaid factor, plant disease is far more common in agricultural areas and is now much more likely to be discovered. These days, monitoring plants in vast and diverse locations has expanded the study of plant condition detection. Farmers experience a great deal of stress when switching from one disease management concept to another. It is possible to automatically identify and categorise illnesses of plant leaves using experimentally evaluated software application services. For novel development, artificial intelligence is used. Utilising machine learning to identify plant disease. Artificial intelligence can be used to start working right away or to give directions on how to complete a task. Understanding training materials and adapting them into forms that should be understandable by humans are the main goals of artificial intelligence. Therefore, we may apply device learning to identify plant diseases. It has aided in making wise decisions and forecasting the vast amount of information produced. The categorization is based on the colour of the leaves, the degree of damage to the fallen leaves, and the position of the dangerous plant falling leaves. Here, we looked at various machine learning algorithms for classifying various plant leaf states and finding those with the highest degree of accuracy.