Theses and Dissertations

ORCID

https://orcid.org/0009-0007-4896-1651

Advisor

Khan, Samee

Committee Member

Malik, Asad

Committee Member

Luo, Yu

Date of Degree

5-16-2025

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Electrical and Computer Engineering

Degree Name

Master of Science (M.S.)

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

The use of unmanned aerial vehicles (UAS) in all industries is steadily increasing every year. To govern the use of UAS, the Federal Aviation Administration (FAA) seeks to provide a foundation of rules and regulations for UAS operation in the National Airspace System (NAS). The UAS Integration Safety and Security Technology Ontology (ISSTO) was developed using the Web Ontology Language (OWL) in 2023. In 2024, a query application was developed to search ISSTO for information about the safety and security of UAS operations. While the application is functional, the search results can be further fine-tuned to match what the user is looking for. The thesis proposes a fine-tuned BERT model for the query application. The model is fine-tuned using the data in ISSTO. It gives the application a better understanding of the taxonomy of the ontology. The integration of machine learning into the query application allows the program to better understand what the user is asking for. The developed model improves the accuracy and efficiency of the query application to become a better tool for UAS operators.

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