IoT-Based Leaf Disease Detection and Alerting System Using K-means Algorithm

Indian agriculture has faced significant challenges due to falling agricultural production caused by widespread plant diseases. Declining agricultural productivity has forced farmers to resort to excessive pesticide usage, posing threats to human and animal life, and contaminating vegetables. This automated disease identification system integrates advanced image processing techniques, Raspberry Pi, and K-means clustering for rapid disease detection. The process involves picture acquisition, processing, segmentation, feature extraction, and disease categorization. Upon detection, the system triggers a buzzer alert and sends emails and SMS notifications to farmers, delivering comprehensive disease information, causes, and remedies through a user-friendly voice assistant in their chosen language. Simultaneously, disease details are dispatched on the screen and sent to the user’s email for future reference. This approach ensures clear communication, aiding farmers in prompt decision-making, minimizing unnecessary pesticide use, and promoting agricultural sustainability. The proposed system offers a precise, real time, and accessible method for disease detection, revolutionizing agricultural practices in India. This solution emphasizes the importance of technological intervention in promoting sustainable agriculture and ensuring food security.