GreenGuard: Mobile Application for Real-Time Tea Leaves Disease Detection and Treatment Guidance

Accurate tea leaves disease detection is essential in agriculture to maintain healthy crops, food security, and economic stability. Tea leaves disease identification is challenging due to traditional detection methods, frequently constrained by the knowledge gap between small-scale and general-level farmers. To alleviate this issue, the proposed study presents an Artificial Intelligence (AI)-enhanced tea plant disease detection system that can accurately identify ailments and suggest relevant treatments. The proposed Convolutional Neural Network (CNN) architecture ensures high accuracy while efficiently working in real time for disease detection and treatment suggesting. The custom CNN model surpasses the ResNet50V2 model's accuracy while achieving 94% accuracy in disease detection. Further, the study initiative promises to make a major contribution to the advancement of agricultural technology in the tea plantation sector and the support of farming-dependent people worldwide by fusing AI with traditional methods while ensuring sustainable development and food security.