Abstract: Crop disease detection system focuses on providing the information about the crop disease prediction, pesticide recommendation and the amount of pesticide or chemicals to be used for an unhealthy crop. The user, who is the Farmer clicks a picture of the unhealthy crop and uploads it to the server by using the android application installed in mobile or by using webpage. After uploading the image the farmer clicks the Predict button which is displayed over screen. Then uploaded image is processed and accordingly the features of that image are extracted from it. Based on these features, classiﬁcation of image is done using Convolutional neural network and the classes having maximum probability is selected for further process. Then the result consisting of the disease name is retrieved and shown to the user. This result is then uploaded into the message table in the server and retrieved in mobile application or on the webpage where corresponding information such as pesticide name, amount of pesticide to be used and organic pesticides which are stored. Now the Farmer will be able to retrieve the complete information in a presentable, readable format on the screen of the Application.
Keywords:Pesticide, classiﬁcation, Extraction, Convolutional neural Networks
| DOI: 10.17148/IJARCCE.2020.9915