An automatic pesticide sprayer to detect the crop disease using machine learning algorithms and spraying pesticide on affected crops

Abstract

In the face of a focus on development, a farming residue a most powerful sector of an Indian financial management system both regarding the benefaction to gross domestic product (GDP) and also the source of utilization to the billions of people across the country. Agriculture is an agribusiness of the farmer that take part in the Indian financial management system. More than 75 percent of farm households depend on agriculture for their livelihood. But pest infestation in crops is a serious problem that slows down the growth of agricultural production. Crop disease identification in the agricultural sector is essential to deal with such problems. This present paper provides a technical solution to solve the type of issue in which the CNN algorithm is used to diagnose crop diseases and involves automatic pesticide spraying to spray pesticides on the affected crops locally. The system is based on pesticide sprays. The design deals with three modules image acquisition, image pre-processing, image segmentation, feature extraction, and classifications, and automatic spraying pesticide on the crop. The suggested system can work from a distance with a laptop with the help of a VNC viewer and Python IDLE.