Rapid Plant Disease Detection Using AI Techniques

India is a country of agriculture where 60 percent of the population, according to the census, 2011 is involved in the agriculture industry. A survey depicts that a huge amount of the worth of the crop gets wasted due to plant disease every year in India. The paper deals with a solution for the problem of plant disease by creating a system that can predict the disease in a plant by referring to the image of the infected plant. The paper aims not only for disease detection but also recommends a treatment for dealing with the disease in the infected plant. The author's team had worked on the PlantVillage dataset for creating the model, which contains a large collection of images of various plant species and their associated diseases. The proposed model uses deep learning technique based on Convolutional Neural Network (CNN) and utilizes the Fast.ai library of Python. The ResNet34 model has been used for the analysis. ResNet34 use Convolutional Neural Network (CNN), with residual learning. Research for the treatment of disease is also conducted, by the author's team. This paper aims to bring our research to the knowledge of every farmer, researcher, and inquisitive who wants to put their efforts into the field of agriculture.