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Publication Date

2024

Document Type

Poster

Degree Type

Graduate

Department

Information Technology

Mentor

Professor Elahe Javadi

Mentor Department

Information Technology

Abstract

Navigating the services and resources of university fitness centers can give challenges to both students and staff. This project introduces a creative solution: an AI-driven chatbot designed specifically for the Redbird Recreation Center at Illinois State University. By using one of the commonly used Python libraries for working with large language models (Lang chain), known for its efficiency in constructing intelligent chatbots, we aim to develop a prototype capable of delivering coherent, context-aware interactions.

Our approach involves gathering information from various sources including documents, staff and student interviews, and user feedback. Through this comprehensive approach, we plan to address usual questions about fitness programs, schedules, and personal recommendations.

Along with this, we prioritize privacy and security measures, ensuring compliance with university policies to safeguard user data.

While this project serves as a proof of concept, future deployment of such a chatbot system will enhance user engagement within the fitness center. It will also increase efficiency and accessibility by providing a user friendly interface for accessing information and automating routine inquiries. Staff will not be answering repetitive inquiries, but will have time to attend to unique, more complicated services and activities that the student may need assistance with.

The project also includes a user experience test to assure information usability. Although our project will be a prototype and will not be alive, we compile a list of methods with which a live version can safeguard user data and assure privacy and security.

In the symposium, we will explain the process for making a chatbot using available large language models. We will also have the system available for interacting with visitors chatbot with sample inputs and collect user feedback during testing phases to identify areas for improvement and iterate on the chatbot's functionality, and will provide a do-it-yourself documentation for anyone who may be interested in exploring this topic further.

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