G. Udaykiran Bhargava, B Tejaswi, L Hemanth, B Dharma Teja, B Sai Chandhu, Sk Aman 03 04(1) Crop disease detection is a critical challenge in modern agriculture that directly impacts food security and crop yield worldwide This Project presents an embedded system for realtime crop disease detection using a Raspberry Pi microcomputer integrated with a USB camera and a deep Convolutional Neural Network CNN model trained on a large dataset of diseased and healthy plant images The proposed system captures images of plant leaves in the field preprocesses them and feeds them through the CNN model to classify the type of disease with high accuracy Results obtained from the system are displayed on a connected LCD screen and simultaneously transmitted to a remote user via a Telegram Bot for immediate notification making it a costeffective and practical solution for realtime agricultural disease monitoring and early intervention Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026