A Small Language Model Framework for Intelligent Agricultural Knowledge Retrieval and Context-Aware Decision Support

DOI

10.2991/978-94-6239-791-0_22How to use a DOI?

Keywords

Small Language Models (SLMs); Agricultural Knowledge Retrieval; Decision Support Systems; Smart Farming; Precision Agriculture; Context-Aware Computing

Abstract

Artificial intelligence is transforming modern agriculture by enabling intelligent advisory services, efficient resource utilization, and data-driven decision-making. However, many language-model-based agricultural systems rely on computationally intensive architectures that are difficult to deploy in resource-constrained farming environments. This paper proposes a Small Language Model (SLM) framework for intelligent agricultural knowledge retrieval and context-aware decision support. The proposed framework integrates natural language query understanding, semantic knowledge retrieval, contextual relevance analysis, and recommendation generation within a lightweight architecture designed for efficient deployment. The agricultural knowledge retrieval layer utilizes domain-specific repositories containing crop, disease, irrigation, fertilizer, and weather information, while a context-awareness mechanism incorporates crop type, environmental conditions, seasonal factors, and symptom descriptions to improve recommendation relevance. An evaluation framework based on retrieval performance, computational efficiency, and deployment-oriented metrics is also presented to facilitate future implementation and assessment. The proposed architecture emphasizes resource efficiency, edge deployment capability, and scalability, making it suitable for agricultural environments with limited computational infrastructure and network connectivity. The framework provides a structured foundation for developing intelligent agricultural advisory systems that combine efficient knowledge retrieval with context-aware decision support for modern smart farming applications.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Mohammed Danish Kolhar
AU  - Abdul Hannan R. Dalal
AU  - Yuvraj Lahoti
PY  - 2026
DA  - 2026/10/09
TI  - A Small Language Model Framework for Intelligent Agricultural Knowledge Retrieval and Context-Aware Decision Support
BT  - Proceedings of the International Conference on Artificial Intelligence and Machine Learning for Agro-Ecosystems (ICAIML-AE 2026)
PB  - Atlantis Press
SP  - 275
EP  - 296
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-791-0_22
DO  - 10.2991/978-94-6239-791-0_22
ID  - Kolhar2026
ER  -