Research Projects

Food security is a significant concern worldwide, with food security expected to reach over $9.7 billion by 2050. Plant diseases pose a significant threat to crop yield and standardized agricultural production, leading to increased grain and vegetable costs and economic losses. In India, plant disease and pest generation account for at least a 15-25% reduction in food grain production. Modern cultivation techniques, globalization, human activities, and climate change all contribute to plant disease infection, making it difficult to control. Tea, the most commonly used agricultural product in India, plays a significant role in the country's economy. Detecting tea plant disease is challenging due to lack of expertise, limited resources, time-consuming inspection, variability of disease patterns, and lack of financial resources. This research aims to design and develop a Deep Learning-based Tea Plant Disease Detection Model, measure its detection accuracy using a generated dataset or benchmark dataset, and convert the model into a web-based tool for Indian farmers and users. The model provides details of the disease to registered users on their mobile devices, ensuring their plants are not suffering from disease and contributing to the country's food security.