Machine Learning-Driven Decision Support for Autonomous Services in Airport Operations

Centered on airport operations, this research utilizes open flight data from multiple airports as a focal point. Collaborating with Aurrigo, the project aims to optimize data acquisition from open sources and construct, train, and thoroughly assess machine learning models for forecasting future airport operations. These predictive capabilities will play a pivotal role in informing decision-making processes regarding the deployment and strategic planning of autonomous services within airport facilities. By integrating advanced predictive analytics powered by machine learning, this project aims to transform the operational efficiency of autonomous services, facilitating cost-effective and strategically informed decision-making across various operational domains.

Faculty Supervisor:

Burak Kantarci

Student:

Partner:

Aurrigo

Discipline:

Computer science

Sector:

Finance and Insurance

University:

University of Ottawa

Program: