Data Collection and Quality: Gathering a comprehensive and high-quality dataset of plant leaf images across various species and disease conditions was challenging. Ensuring the dataset's diversity and accuracy was crucial for the effectiveness of the AI models.

AI Model Accuracy: Developing AI models that can accurately identify plant species and diagnose diseases from leaf images involved complex algorithmic challenges. Achieving high levels of accuracy and reliability required extensive testing and refinement.

Integration of Diverse Features: Combining diagnostic tools, a knowledge database, community features, and e-commerce into a seamless user experience presented technical and design challenges. Ensuring smooth functionality across these components was essential for user satisfaction.

User Accessibility and Engagement: Making the platform accessible and intuitive for all users, regardless of their technical savvy or agricultural knowledge, was a priority. Engaging users in the community and encouraging active participation posed additional challenges.