Multimodal AI-Powered Local Language Health Advisor for Rural India: Integrating Large Language Models, Voice Recognition, and Visual Augmentation for Equitable Healthcare Access

作者：R. K, V. Jethose, K. R, Hisana Serin K. V, F. J, Paul Jothi G · 发表于：2026 Second International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI) · 年份：2026 · DOI：10.1109/ICMSCI67830.2026.11469563

The availability of quality healthcare information in the rural and non-English speaking areas of India has continued to be a critical challenge as a result of language barriers as well as the low availability of medical professionals. The project is a proposal of an AI-Powered Local Language Health Advisor, which is an attempt to use a Large Language Model (LLM) to provide accessible, accurate, and personalized health suggestions in 22 regional languages in India. The system will offer conversational symptom check, condition selection, personalized health guidance, and self-care suggestions with an added capability of medicine reminder. Populations with less literacy can be made easier to use with optional whisper API voice recognition and DALL-E visual aid generation. The algorithm is a fusion of state-of-the-art image natural language processing, multi-lingual data processing, and culture-aware dialogue generation in order to guarantee accurate and culturally sensitive communications. This solution provides opportunity to underserved communities, hastens the process of early diagnosis, helps people make informed health choices and enhances equitable access to healthcare among the diverse rural communities in India by providing a bridge of linguistic and informational disparities.