Apply Machine Learning with Smartphones to Detect and Recommend the Right Treatment for Plant Diseases

Abstract

Plant sicknesses cause significant harvest creation misfortunes around the world, and a great deal of huge exploration exertion has been coordinated toward making plant infection distinguishing proof and therapy methods more viable. It would be of extraordinary advantage to ranchers to have the option to use the ongoing innovation to use the difficulties confronting horticultural creation and thus further develop crop creation and activity productivity. In this work, we planned and executed an easy-to-understand cell phone-based plant illness discovery and treatment suggestion framework utilizing AI (ML) methods. CNN was utilized for include extraction while the ANN and KNN were utilized to order the plant infections; a substance-based sifting proposal calculation was utilized to recommend significant medicines for the recognized plant illnesses after grouping. The aftereffect of the execution shows that the framework accurately identified and suggested treatment for plant illnesses.