Published Paper Details:

Agriculture, a fundamental human necessity from ancient times, remains crucial for our sustenance. Throughout history, plants have been our primary food source. Today, agriculture continues to be a vital aspect of our lives, serving as the backbone of various economies, irrespective of their developmental stages. Agriculture faces a significant challenge in the form of plant diseases and their impact on trade. Detecting and managing these diseases in a timely manner is crucial for crop health. Plant diseases are defined as natural issues that afflict plants, impeding their growth and potentially causing plant death in severe cases. In modern farming, new technology like IoT and automation can be super helpful. It's really important to keep plants healthy and check their surroundings to catch diseases early and get a good crop. We use smart tools like artificial intelligence (AI) and deep learning to look at plant pictures and find diseases. AI makes the job faster and helps us spot sick plants and control the farm's conditions. Scientists did some research and found out that these technologies are great at finding plant diseases by looking at the leaves. In this project we propose a deep neural network that would be trained to classify a variety of plant diseases. We intend to use PLANT VILLAGE dataset to train the model for the purpose of classification. Plant village consists of almost 16,000 images of leaves(some sick, some healthy) covering 19 different plant diseases.