Application of AI Technology and Image Processing to Smart Agriculture: Detection and Classification of Plant Diseases

Every country's fundamental necessity is agricultural products. Infected plants have a detrimental impact on agricultural output and economic assets in the country. According to previous research, 68% of agricultural productivity is lost, and this is attributed only to the rising incidence of plant leaf disease losses. To solve this significant problem, the screening strategy can be used to diagnosis disease from the photos captured. We've used certain sorts of plants in our research, such as and potatoes, peppers and tomatoes. This procedure included preprocessing, image segmentation, and feature extraction. On the basis of the results of these three steps, the K Nearest Neighbor (KNN) classification is implemented. As a consequence, we had outstanding accuracy (98.23%) in predicting plant leaf diseases across all data sets.