IOT control technology for disease management in agriculture field using image processing -

IOT control technology for disease management in agriculture field using image processing

Automate plant monitoring and smart gardening through IOT in the Arduino Mega Platform. Identifying diseases in plants leave and detect the type of disease by use of image processing. Image Processing steps are pre-processing, spot segmentation and features extraction, and classification. The extracted features are optimized by genetic algorithm and classified by KNN Classifier. In this study they tested for four types of apple plant disease including healthy leaves, Black Rot, Rust, and Scab. In IOT module set the data according to processing steps by comparing the healthy leaves with diseased leaves. For every leaf disease the affected spot will be different.  Based on these data of different leaf images and the spots identified the diseases and provided solution on spot only. Once disease is identified in IOT module in every stages provided a pesticide solution which will displayed in the LCD Display and the same is sent to the farmer mobile with the help of GSM. Based on the recommendation farmers load the pesticides then the IOT module starts to spray the solution according to required dose which was pre filled in data.  All the Stages are monitored in an IOT Webpage. It also monitored soil pH level, climatic conditions, auto irrigation based on requirements. In this module used for apple based on data and it can be improved for other fruits, vegetable and plantation crops.

Citation:

Manjula, G., Visu, P. and Chakaravarthi, S., 2021. IOT Enabled Weedicide Control Using Image Processing at Agriculture Field. EAI Endorsed Transactions on Smart Cities, p.e10.