Revolutionizing Agriculture: A Mobile App for Rapid Plant Disease Prediction and Sustainable Food Security

In order to maintain the health of crops and the quality of the yield they offer, it is very important to diagnose plant illnesses in a timely manner and conduct quality assessments of them. A number of diseases, including bacterial spots, late blight, and leaf mold, amongst others, have the potential to have a detrimental influence on plant production. The primary goal of this research is to develop a mobile application that uses a deep learning model and can predict leaf diseases. In this investigation, a convolutional neural network, more commonly referred to as a CNN, is used on a dataset that includes images that the researchers themselves collected as well as photographs of diverse plant leaves that were acquired from the collection that is stored at Plant Village. In other words, the pictures in the dataset come from two different sources. Using the CNN model, accurate predictions have been produced in excess of 94% of the time.