Date of Submission
2025
Date of Award
6-11-2025
Institute Name (Publisher)
Indian Statistical Institute
Document Type
Master's Dissertation
Degree Name
Master of Technology
Subject Name
Computer Science
Department
Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)
Supervisor
Bhattacharya, Ujjwal
Abstract (Summary of the Work)
Effective pest identification and management are essential for ensuring agricultural productivity, especially in regions with limited expert access. This work proposes a virtual assistant based on a Retrieval-Augmented Generation (RAG) [1] framework to support pest management tasks. The system utilizes a multimodal dataset consisting of pest images and annotated textual interactions, adapted from the AgriLLaVA corpus [2]. The assistant combines retrieval mechanisms with generative language models to generate contextually grounded responses. It is designed for deployment on local hardware with limited computational resources, integrating open-source models for both retrieval and generation. Preliminary results suggest that this approach can provide accurate, scalable, and interpretable support for field-level pest diagnostics.
Control Number
CS2334
DOI
https://dspace.isical.ac.in/items/0f67358f-402e-43c1-b39a-4cbd6c6048be
DSpace Identifier
http://hdl.handle.net/10263/7566
Recommended Citation
Karri, Viswanada Chakravarthy, "Virtual Assistant for Pest Management" (2025). Master’s Dissertations. 443.
https://digitalcommons.isical.ac.in/masters-dissertations/443