Abstract: Artificial intelligence-based advisory systems are increasingly being explored as tools to improve agricultural decision-making; however, many existing solutions assume sta- ble connectivity, uniform user literacy, and low-risk operating conditions. Such assumptions limit their applicability in rural farming environments, where language diversity, infrastruc- ture constraints, and advisory errors can significantly impact livelihoods and ecological sustainability. This paper proposes a context-adaptive agricultural advisory framework implemented through a conversational interface, designed to support farmers operating under low-connectivity and low-literacy conditions.....
Key Word: Agricultural advisory systems, context-adaptive AI, conversational interfaces, rural agriculture, decision support systems
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