AI-Driven Virtual Repository of Medicinal Herbs in AYUSH

Medicinal plants constitute the core therapeutic resources of the AYUSH systems—Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy—where plant-based formulations play a central role in both preventive healthcare and disease management. Despite their long-standing clinical relevance, knowledge related to medicinal herbs remains dispersed across classical texts, regional practices, herbaria records, oral traditions, and isolated digital sources. This fragmentation often results in difficulties related to correct plant identification, quality standardization, dosage safety, and evidence-based application. To address these limitations, this study presents the development of HerboAI, an AI-enabled Virtual Depository of Medicinal Herbs designed as a unified, multilingual, and scalable knowledge platform. The proposed system consolidates structured and unstructured herbal information using a combination of artificial intelligence techniques, including computer vision for image-based plant species recognition, natural language processing for extracting medicinal properties from textual sources, and ontology-driven knowledge graphs for semantic integration of heterogeneous data. A modular three-layer architecture has been realized, consisting of an intuitive web-based user interface, an AI-driven middleware supporting semantic search and reasoning, and a structured herbal database aligned with established AYUSH guidelines. The platform is designed to serve both domain experts and non-specialist users by enabling natural language interaction and providing validated, context-aware responses supported by curated sources. Experimental evaluation confirms the practical viability of deploying offline AI workflows for herbal image identification, semantic information retrieval, and recommendation support, with consistently high precision and user usability. Beyond its technical contributions, the proposed system offers broader value in supporting phytopharmaceutical research, protecting endangered medicinal species, minimizing adulteration risks, and digitally preserving traditional knowledge within appropriate ethical, legal, and regulatory frameworks.