A Campus-Wide AI-Driven Information Retrieval and Support System for Igbinedion University Okada
Abstract
The rapid advancement of Artificial Intelligence (AI) has significantly transformed information retrieval, making it more efficient, interactive, and context-aware. This project addressed the limitations of the existing information retrieval system at Igbinedion University, Okada, which did not keep pace with the capabilities offered by modern AI technologies. To overcome these shortcomings, a campus-wide AI-Driven Information Retrieval and Support System was developed. This solution leverages Retrieval-Augmented Generation and AI-powered Natural Language Processing to provide accurate, context-sensitive responses to queries. The system integrates a vector database and an intuitive web interface, implemented using JavaScript, to process and retrieve data efficiently from diverse university sources. The Structured Systems Analysis and Design Methodology was adopted to guide the project through all phases from feasibility study to implementation and testing. This AI-driven solution was designed to enhance access to university resources and provide a scalable foundation for future features, ultimately bridging the gap between users and institutional information.
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