Abstract: In this world agriculture being the backbone of every developed as well as developing nation. Even though agriculture is our essential source of income and food serving, still farmers faced numerous difficulties due to climate change, degradation of soil quality, moisture, pests, weeds and food security problems. Especially plant infection/disease is one of the ongoing challenges for farmers, which imposes a threat on income and food security. Artificial Intelligence in agriculture has brought an agriculture revolution. This technology has prediction the pest infection and protects the crop from diseases by informing the farmers about the steps to be taken. The classification of the crops is done on the basis of their images by using image processing method and convolutional neural networks are applied to differentiate the healthy crops from the ones that are infected from some disease. Disease detection involves the steps like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This paper discussed the methods used for the detection of plant diseases using their leaves images. Further, based on the disease detected the required amount of the pesticide and their quantities are calculated to help farmers in making fast solution. The experiment is evaluated for paddy leaf and its various diseases are identified using MATLAB tool. The analyzed data will be transmitted as an SMS send to the user by PIC microcontroller. The objective of this project is to solve the problem novel way by early detection and elimination of pests with time-effective manner and gives more accurate results.
Keywords: Image Acquisition, Segmentation, Feature extraction, CNN, Microcontroller
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