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Computer Science > Emerging Technologies

arXiv:2409.08916 (cs)
[Submitted on 13 Sep 2024 (v1), last revised 8 Oct 2024 (this version, v2)]

Title:Farmer.Chat: Scaling AI-Powered Agricultural Services for Smallholder Farmers

Authors:Namita Singh, Jacqueline Wang'ombe, Nereah Okanga, Tetyana Zelenska, Jona Repishti, Jayasankar G K, Sanjeev Mishra, Rajsekar Manokaran, Vineet Singh, Mohammed Irfan Rafiq, Rikin Gandhi, Akshay Nambi
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Abstract:Small and medium-sized agricultural holders face challenges like limited access to localized, timely information, impacting productivity and sustainability. Traditional extension services, which rely on in-person agents, struggle with scalability and timely delivery, especially in remote areas. We introduce FarmerChat, a generative AI-powered chatbot designed to address these issues. Leveraging Generative AI, FarmerChat offers personalized, reliable, and contextually relevant advice, overcoming limitations of previous chatbots in deterministic dialogue flows, language support, and unstructured data processing. Deployed in four countries, FarmerChat has engaged over 15,000 farmers and answered over 300,000 queries. This paper highlights how FarmerChat's innovative use of GenAI enhances agricultural service scalability and effectiveness. Our evaluation, combining quantitative analysis and qualitative insights, highlights FarmerChat's effectiveness in improving farming practices, enhancing trust, response quality, and user engagement.
Comments: 35 pages
Subjects: Emerging Technologies (cs.ET); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC)
Cite as: arXiv:2409.08916 [cs.ET]
  (or arXiv:2409.08916v2 [cs.ET] for this version)
  https://doi.org/10.48550/arXiv.2409.08916

Submission history

From: Akshay Nambi [view email]
[v1] Fri, 13 Sep 2024 15:31:33 UTC (5,736 KB)
[v2] Tue, 8 Oct 2024 06:03:41 UTC (5,736 KB)
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