Location

https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php

Document Type

Event

Start Date

22-4-2026 4:00 PM

Description

This project includes the design and validation of a metadata-driven media intake and organization system implemented for the Office of the District Attorney, Cobb Judicial Circuit. The institution produces a considerable volume of photographs and video content via outreach programs and community interaction initiatives. Yet, the organization does not have an organized framework for managing media files, which results in inefficient file retrieval and data loss over time due to a lack of standardized organizational practices. In this regard, this project aims to develop a workflow-based system for the efficient organization of media files that will be powered by a local user interface and backed up by an intake process on the backend. First, the system will automate the metadata extraction process, classify all files based on events and the date range of their creation, and provide the necessary guidance on filling out the questionnaire to apply metadata consistently. Next, the optional AI-based tagging mechanism will help improve the metadata content by providing recommendations, ensuring that humans double-check the suggested changes. The system will allow integration with the Microsoft 365 SharePoint platform and its metadata management features to facilitate efficient media searching and filtering. Considering the access restrictions, the proof-of-concept was implemented in a mock SharePoint environment.

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Apr 22nd, 4:00 PM

UC-149-185 AI-Assisted Media Organization and Intake System

https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php

This project includes the design and validation of a metadata-driven media intake and organization system implemented for the Office of the District Attorney, Cobb Judicial Circuit. The institution produces a considerable volume of photographs and video content via outreach programs and community interaction initiatives. Yet, the organization does not have an organized framework for managing media files, which results in inefficient file retrieval and data loss over time due to a lack of standardized organizational practices. In this regard, this project aims to develop a workflow-based system for the efficient organization of media files that will be powered by a local user interface and backed up by an intake process on the backend. First, the system will automate the metadata extraction process, classify all files based on events and the date range of their creation, and provide the necessary guidance on filling out the questionnaire to apply metadata consistently. Next, the optional AI-based tagging mechanism will help improve the metadata content by providing recommendations, ensuring that humans double-check the suggested changes. The system will allow integration with the Microsoft 365 SharePoint platform and its metadata management features to facilitate efficient media searching and filtering. Considering the access restrictions, the proof-of-concept was implemented in a mock SharePoint environment.