We present Kissan-Dost, a multilingual, sensor-grounded conversational system that turns live on-farm measurements and weather into plain-language guidance delivered over WhatsApp text or voice. The system couples commodity soil and climate sensors with retrieval-augmented generation, then enforces grounding, traceability, and proactive alerts through a modular pipeline. In a 90-day, two-site pilot with five participants, we ran three phases (baseline, dashboard only, chatbot only). Dashboard engagement was sporadic and faded, while the chatbot was used nearly daily and informed concrete actions. Controlled tests on 99 sensor-grounded crop queries achieved over 90 percent correctness with subsecond end-to-end latency, alongside high-quality translation outputs. Results show that careful last-mile integration, not novel circuitry, unlocks the latent value of existing Agri-IoT for smallholders.

翻译：我们介绍Kissan-Dost，一个多语言、基于传感器数据的对话式系统，它能将实时的农田测量数据和天气信息转化为通俗易懂的指导建议，并通过WhatsApp文本或语音进行推送。该系统将商用土壤与气候传感器与检索增强生成技术相结合，并通过模块化流水线确保信息基于数据、可追溯，并能主动发出警报。在一项为期90天、覆盖两个地点、涉及五名参与者的试点研究中，我们进行了三个阶段（基线、仅仪表板、仅聊天机器人）。仪表板的使用是零星的且逐渐减少，而聊天机器人则几乎每天被使用，并为具体行动提供了信息。在99个基于传感器的作物相关查询的受控测试中，系统实现了超过90%的正确率，端到端延迟低于一秒，同时提供了高质量的翻译输出。结果表明，对于小农户而言，释放现有农业物联网潜在价值的关键在于审慎的“最后一公里”整合，而非新颖的硬件电路。