MACHINE LEARNING BASED SMART CROP DISEASE DETECTION (KEY IJP************629)

• Hrishikesh Vinod Deshmukh,Prathmesh Manojrao Ugale,Abizer Tayyeb Fakhri

Abstract

Here we discussed a system using ML model for the detection and prevention of diseases of plants from getting spread. For the image analysis, the CNN algorithm is used. It has many advantages for the use in big farms of crops. It automatically detects signs of disease whenever they appear on leaves of the plant. In pharmaceutical research, leaf disease detection is necessary and an important topic for research because it has advantages in monitoring crops in the farm and thus it automatically detects symptoms of disease by image processing by CNN algorithm. This report provides the best method for detection of plant diseases using image processing and also shows fertilizer on it. And also shows sensor results in particular areas, displaying the name of the disease, fertilizer and sensors result on the monitor display. To upgrade agricultural products, automatic detection of disease symptoms is useful. This will lead to an increase in productivity of farming.