Published Paper Details:

The Machine Learning (ML) field has gained its momentum in almost any domain of research and just recently has become a reliable tool in the medical domain. Identification of the plant diseases is the key to prevent the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the study of visually observed patterns seen on the plant. Health monitoring and disease detection on the plant is very critical for the substantial growth. It is very difficult to identify the diseases on the plant manually and provide the treatment for that appropriate disease. It requires a tremendous amount of work experience and should be expertise in the plant diseases and also requires excessive time for processing. Here in this proposed application we try to find out the disease of the plant based on the inputs which we observe physically on any plant. For any plant there are 5 levels of disease occurrences: Stem Level, Leaves Level, Seed Level,Lessions Level, Plant Level. So any disease on the plant can be either of these five levels. We try to design an medical dictionary in which all the physical inputs are substituted according to any of the level and then try to detect which disease plant is suffered with and it will try to provide cure for that appropriate disease. Our evaluation results on the proposed method using ML approach for identifying diseases on plant able to identify the diseases accurately and try to provide a solution for the end users.