9th International Conference on ICT for Sustainable Development

Authors - Sneh Soni, Mahek Siroya, Rutva Shingala, Purvi Prajapati, Madhav Ajwalia, Hemant Yadav
Abstract - A growing challenge in agriculture is identifying new cases of new cases of fungal-caused plant diseases, which is made even worse by the consistently changing climate and its unpredictable impacts These diseases are among the biggest threats to agriculture as they lower the quality of crops, undermine the sustainability of farming, cause financial losses, and lead to nutritional deficiency. In fact, the agricultural sector suffers substantial annual losses, with pests affecting up to 20–40% of global productivity. In this research, we aim to tackle this very problem using state-of-the-art technologies. We are particularly using Convolutional Neural Networks (CNNs) and Deep Learning, a subset of artificial intelligence, to automate the detection and classification of mango leaf diseases. Through these innovative technologies, we seek to not only enhance the techniques of disease management but also drastically cut crop losses, which will lead to the sustainability and resilience of agricultural systems across the globe.