Aerial Imagery for Plant Disease Detection by Using Machine Learning of Typical Crops in Marathwada

Abstract

Agriculture plays an important role by contributing to the economy of India. 75% of the population has agriculture as their major occupation and only source of income. There are various parts in the process of production where we need to pay more attention to the higher productivity of crops. Many farmers face loss in yields every year due to diseases affecting the crops. A fast and automated system to detect the diseases on crops in the early stage can be very helpful in such situations. Having such a vast variety of types of crops grown in India, we will focus on cotton and turmeric crops in the Marathwada region, Maharashtra, India. Our proposed system aims to develop an auto-guided drone that can take the images of crop leaves as input. These images will then be processed by applying Convolutional Neural Network (CNN) to detect the diseases which are affecting the crops. This system will also help mark the most affected regions of fields. By using this system, we can increase the productivity of the crop