Cotton Leaf Disease Detection Using Artificial Intelligence with Autonomous Alerting System

One of India’s most well-known commercial crops is cotton. Due to the disease’s invasion, cotton production has decreased. These plant diseases are typically brought on by Bacteria, fungi, or other pests, which can significantly impair productivity if they are not controlled right away. Cotton plant leaf diseases need to be precisely recognized at an early stage and should be taken care of at a faster rate to reduce the loss. This article mainly contributes to providing a solution with the development of automated systems and summarizes the effects of environmental factors on illnesses of cotton plants and an analysis of the relationships between these diseases and other environmental factors. To initiate an advancement in the field of agriculture by implementing autonomous systems. The research also focuses on the CNN-based deep learning approach required for precise disease prediction and diagnosis to stop the spread of illnesses in cotton plants and reduce cotton output loss. Our experimental results show an accuracy of 99.997% prediction of cotton diseases using CNN algorithm.