mlsanityData to 7 Oct 2026

Kissan-Dost: Bridging the Last Mile in Smallholder Precision Agriculture with Conversational IoT

arXiv 2602.08593 ↗First posted 9 Feb 2026cs.HC cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 14 of its 42 references that are in the map. First posted on arXiv 9 Feb 2026.

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14 of 42 references.

References · 14

  1. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  2. 2024From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judgecited by 480
  3. 2023Ragas: Automated Evaluation of Retrieval Augmented Generationcited by 408
  4. 2024Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Modelscited by 301
  5. 2022CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Taskcited by 205
  6. 2018Deep learning in agriculture: A surveycited by 160
  7. 2024RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generationcited by 144
  8. 2024MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Taskcited by 92
  9. 2023Do Multilingual Language Models Think Better in English?cited by 87
  10. 2024Generative AI for Synthetic Data Generation: Methods, Challenges and the Futurecited by 31
  11. 2024DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generationcited by 16
  12. 2024Farmer.Chat: Scaling AI-Powered Agricultural Services for Smallholder Farmerscited by 12
2 more
  1. 2024Quantitative Insights into Large Language Model Usage and Trust in Academia: An Empirical Studycited by 2
  2. 2024Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preferencecited by 2

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  1. 2025Building AI-based advisory services for smallholder farmers: Technical learnings from the AIEP Initiative ↗
  2. 2025Leveraging LLMs for Mission Planning in Precision Agriculture
  3. 2025Intent Aware Context Retrieval for Multi-Turn Agricultural Question Answering
  4. 2026Crop Recommendation and Agricultural Query Answering System Using Spatio-Temporal Graph Neural Networks and Hybrid Retrieval Augmentation
  5. 2026Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing
  6. 2026AgriWorld:A World Tools Protocol Framework for Verifiable Agricultural Reasoning with Code-Executing LLM Agents
  7. 2025AgroLLM: Connecting Farmers and Agricultural Practices through Large Language Models for Enhanced Knowledge Transfer and Practical Application
  8. 2025A Multimodal Conversational Assistant for the Characterization of Agricultural Plots from Geospatial Open Data