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RAG-Based Food Processing Knowledge Assistant for Quality Control

This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction ‘RAG-Based Food Processing Knowledge Assistant for Quality Control’. The project connects agricultural engineering with artificial intelligence, machine learning, deep…

Project Overview This B.Tech Agricultural Engineering project is based on the recent AI/ML research direction 'RAG-Based Food Processing Knowledge Assistant for Quality Control'. The project connects agricultural engineering with artificial intelligence, machine learning, deep learning, IoT, computer vision, drone analytics, or RAG-style decision support. Students can use the linked 2023-onward paper/source as the academic base and convert it into an implementation-focused final-year project with sensors, datasets, dashboards, mobile/web interfaces, prediction models, or prototype automation.
Research Paper Title RAG-Based Food Processing Knowledge Assistant for Quality Control
Research Paper / PDF Link Open Paper / PDF
Year 2024
Project Area Food Processing Projects
Project Type RAG Food Assistant
Required Tools / Software Python, Pandas, Scikit-learn, TensorFlow/PyTorch, Streamlit/Flask, IoT dataset/sensor data
Main Features / Working Principle Build a RAG assistant that answers food processing and quality-control queries from uploaded documents
Expected Output A document-based AI assistant for food processing guidance
Possible Add-ons Add citations and SOP retrieval
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This B.Tech agricultural engineering project resource helps students connect a recent AI-based research direction with a practical implementation plan, tools, expected output, and possible extensions.

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