Overcoming LLM Challenges using RAG-Driven Precision in Coffee Leaf Disease Remediation

TL;DR

This paper presents a novel AI system combining YOLOv8 and RAG to improve disease diagnosis and remediation in coffee agriculture, addressing LLM limitations and promoting sustainable farming practices.

Contribution

It introduces an integrated AI framework using object detection and RAG to enhance disease identification and reduce LLM hallucinations in precision agriculture.

Findings

Effective real-time disease detection in coffee crops

Reduced reliance on pesticides through precise diagnosis

Enhanced system adaptability in diverse agricultural settings

Abstract

This research introduces an innovative AI-driven precision agriculture system, leveraging YOLOv8 for disease identification and Retrieval Augmented Generation (RAG) for context-aware diagnosis. Focused on addressing the challenges of diseases affecting the coffee production sector in Karnataka, The system integrates sophisticated object detection techniques with language models to address the inherent constraints associated with Large Language Models (LLMs). Our methodology not only tackles the issue of hallucinations in LLMs, but also introduces dynamic disease identification and remediation strategies. Real-time monitoring, collaborative dataset expansion, and organizational involvement ensure the system's adaptability in diverse agricultural settings. The effect of the suggested system extends beyond automation, aiming to secure food supplies, protect livelihoods, and promote eco-friendly farming practices. By facilitating precise disease identification, the system contributes to sustainable and environmentally conscious agriculture, reducing reliance on pesticides. Looking to the future, the project envisions continuous development in RAG-integrated object detection systems, emphasizing scalability, reliability, and usability. This research strives to be a beacon for positive change in agriculture, aligning with global efforts toward sustainable and technologically enhanced food production.