Smart Agriculture: Leaf Disease Detection And Curative Counsel Using Ecnnpld

Abstract

India is an agricultural country where 70% people depend on agriculture. Hence economically, India highly depends on crop production. Plants are not always healthy, diseases in plants can be regarded as a critical factor which causes the reduction in crop yield and this is the major rationale for early disease detection in plants. Appropriate measures on disease identification should be introduced to prevent the issues and minimise the losses. Regular monitoring and authentic disease identification in initial stages of plant growth can increase the quantity and quality of crop yield. Application of technical algorithm correlating the machine vision and mobile vision is actively explored for the sake of achieving the intelligence farming by early plant disease detection. A mobile application is obviously desirable to aid the farmers or garden enthusiasts in diagnosing the sorts of plant ailments. Although some similar applications exist, most of them achieve the function by submitting the image to a team of plant pathologists or expert garden advisors to get possible identification results and some advices. In this paper the study of android application based on image processing and remedy classification techniques used for the detection of plants by observing the symptoms on leaves is presented. The application named as ECNNPLD prediction app turns out to be user friendly to capture the leaf images from mobile camera to process the pre-processing stage, segmentation stage, and post processing stage to predict the diseases.  Proposed research work also trained remedies for classified diseases. Application directly suggests curatives to the farmer for the purpose of crop protection. Further, it also focuses on enhanced Convolutional neural network (ECNN) which is one among the CNN based powerful classification techniques.