T.Naga Pavan, K.Akhil Kumar, V.Dharani, Sk.Asma, Mrs. T. Tejaswi 03 04 The Automated Pest and Disease Detection System leverages advanced computer vision and deep learning to mitigate the limitations of manual agricultural monitoring such as human error and delayed intervention By integrating Convolutional Neural Networks CNN for precise disease classification and the YOLO You Only Look Once framework for realtime pest localization the system transforms raw crop imagery into actionable diagnostic data This automated approach facilitates earlystage detection and targeted pesticide application significantly reducing economic losses while promoting environmental sustainability Ultimately the project bridges the gap between expert knowledge and fieldlevel implementation providing a scalable solution for modernizing global food security through datadriven precision agriculture Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026