Pilot study demonstrates 91% intent recognition and 89% advice correctness in Tamil-speaking farmers, indicating AI chatbot's potential in agricultural support.
Smallholder farmers in Tamil Nadu often face challenges accessing timely agricultural advice due to language barriers, low literacy, and inconsistent extension services. This paper presents the development of an AI-powered voice chatbot that converses fluently in Tamil, providing crop-specific guidance in irrigation, pest control, fertilizer application, and weather-driven decision-making. The system integrates Tamil NLP, speech recognition, and a structured knowledge base. It supports multiple access channels, including an Android mobile app, WhatsApp API, and optional IVR. A pilot study involving 50 local farmers demonstrated approximately 91 % intent recognition accuracy, roughly 89 % agronomic advice correctness, a user satisfaction rating of 4.3 out of 5, and a 72 % adoption rate of recommended practices. We discuss the architecture, methodology, field insights, and prospects for expansion. This solution fosters digital inclusion by empowering Tamil-speaking farmers with voice-first technology. Keywords - Agricultural Chatbot, Tamil Language, Voice Interface, NLP, Agri‑Advisory.
No takes yet. Share an insight, caveat, or question.
Prabhu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: