Identification of plant diseases using ML model with mobile application

Abstract

Plant diseases have been a significant aspect in the decreased crop production over the years. Ultimately they cause the farmers a decline in the profit which they earn from their annual harvest. This problematic scenario can be avoided if the fields are monitored closely right from the beginning, planting stage until the end, harvesting stage. But this method is only applicable if the crops have been planted at a small-scaled farm. The proposed system in this project is going to assist the farmers in looking out for plant leaf diseases such as black rot, leaf blight or bacterial spot etc among their fields before things get out of hand. The system is based on disease identification and their classification by employing a trained Machine Learning model. This model has been trained using "Plant Disease Data-set" openly available at Kaggle. The model can be called into play via mobile application having access of its camera. Just as the model is done with its pre-processing, it will return its result that will be forwarded to the user via the mobile application. If the result comes out positive the farmer can take precautionary measures before the disease spreads in the whole field.