Tamil-Based Mobile Application for the Identification of Anthurium Plant Diseases

This paper introduces a novel approach to address the challenges faced by Tamil-speaking farmers in identifying Anthurium plant diseases by presenting a Tamil-based mobile application developed using React Native framework integrated with machine learning algorithms. The application aims to empower farmers by providing them with a user-friendly tool for accurate disease identification and management. Leveraging the capabilities of React Native, the application ensures cross-platform compatibility and seamless performance on both Android and iOS devices. The machine learning component of the application utilizes deep learning techniques to analyze images of Anthurium plants captured through the mobile device’s camera, enabling real-time disease detection. By incorporating Tamil language support, the application caters to the linguistic preferences of the target user base, enhancing accessibility and usability. This research outlines the design architecture of the mobile application, elucidates the implementation of machine learning algorithms for disease identification, and evaluates the performance of the system through rigorous testing and validation. Preliminary results demonstrate promising accuracy in disease detection, indicating the potential of the developed application to significantly improve Anthurium cultivation practices in Tamil-speaking regions. This study contributes to the convergence of mobile technology, machine learning, and agriculture, offering a practical solution to address the specific needs of farmers in disease management while fostering digital inclusivity through Tamil language localization.