Liam Cotter as the winner of the ITS Bursary 2026 of Intelligent Transport Systems in the field of mobility
ITS Ireland would like to acknowledge Liam Cotter as the winner of the ITS Bursary 2026 of Intelligent Transport Systems in the field of mobility.
The ITS Ireland Project evaluation committee of Paschal Griffin, David O Keeffe and Aidan Mahony would like to commend all the students they visited in University College Cork during the project Open Day on the standard of their final year projects and wish them all the best in their future careers. This ITS Ireland annual Bursary is provided to Final year Projects with a focus on mobility in the School of Computer Science and Information Technology in UCC and is provided by ITS Ireland in effort to promote solutions, research and careers in intelligent transport systems in Ireland
Liam is currently completing his BScCS and his project GhostBUSter involved A Machine Learning-Powered Application for Real-Time Bus Arrival Prediction
Details as follows:
"Ghost Buses" - scheduled buses that appear on the digital displays at bus stops but never actually arrive - are a frequent frustration for commuters in Ireland.
GhostBUSter is a machine learning powered solution designed to eliminate this uncertainty by providing realistic predictions of when the bus will arrive.
The primary objective of the project was to develop an application that leverages National Transport Authority data to forecast bus arrivals around Cork. At its core, the system uses a neural network trained on
historical real-time data to generate predictions. By filtering out buses that have been cancelled, deviated from their official route or lost tracking mid-transit, the application ensures that predictions are only made
for buses likely to reach the user. The data is served via a Progressive Web App, offering the seamless experience of both a website and a dedicated mobile application. Ultimately, GhostBUSter gives regular
commuters a simple, fast, and reliable way to check their bus arrival times without the usual uncertainty or hassle.