2026
Yeaminur Rahman; Juliano Franz; Rezwana Mahfuza; Sue Molloy; Derek Reilly
Adapting Eco-Driving Feedback and Historical Visualization for Vessel Dashboards Proceedings Article Forthcoming
In: Proceedings of the 2026 IEEE 29th International Conference on Intelligent Transportation Systems (ITSC), IEEE, Forthcoming.
BibTeX | Tags: design, feedforward, geospatial analytics, itinerary planning, mobile, navigation, training, visualization
@inproceedings{nokey,
title = {Adapting Eco-Driving Feedback and Historical Visualization for Vessel Dashboards},
author = {Yeaminur Rahman and Juliano Franz and Rezwana Mahfuza and Sue Molloy and Derek Reilly},
year = {2026},
date = {2026-09-07},
booktitle = {Proceedings of the 2026 IEEE 29th International Conference on Intelligent Transportation Systems (ITSC)},
publisher = {IEEE},
keywords = {design, feedforward, geospatial analytics, itinerary planning, mobile, navigation, training, visualization},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
Ramanpreet Kaur; Sathaporn Hu; Hariprashanth Deivasigamani; Nirmal Adhikari; Derek Reilly
ViSSTA: a Hybrid Tablet and Augmented Reality Interface for Space Syntax Data Analysis Proceedings Article Forthcoming
In: Proceedings of the 15th International Space Syntax Symposium, Forthcoming.
BibTeX | Tags: 3-D user interface, architecture, augmented reality, geospatial analytics, space syntax, touchscreen, visualization
@inproceedings{nokey,
title = {ViSSTA: a Hybrid Tablet and Augmented Reality Interface for Space Syntax Data Analysis},
author = {Ramanpreet Kaur and Sathaporn Hu and Hariprashanth Deivasigamani and Nirmal Adhikari and Derek Reilly},
year = {2026},
date = {2026-06-08},
urldate = {2026-06-08},
booktitle = {Proceedings of the 15th International Space Syntax Symposium},
keywords = {3-D user interface, architecture, augmented reality, geospatial analytics, space syntax, touchscreen, visualization},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
2025
Yeaminur Rahman
Adapting Eco-Driving Feedback and Historical Visualization for Vessel Dashboards Masters Thesis
2025.
Abstract | Links | BibTeX | Tags: behaviour change, climate, dashboard, geospatial analytics, mobile, navigation, peripheral vision, simulation, training, virtual environment, visualization, wayfinding
@mastersthesis{nokey,
title = {Adapting Eco-Driving Feedback and Historical Visualization for Vessel Dashboards},
author = {Yeaminur Rahman},
url = {https://hdl.handle.net/10222/85531},
year = {2025},
date = {2025-11-25},
urldate = {2025-11-25},
abstract = {Maritime navigation is a significant source of greenhouse gas emissions. While large-scale cargo shipping is the major contributor, smaller maritime operations, including patrolling, fishing, public transit, and recreation, present unique challenges and opportunities for power management. Fuel consumption, power conversion, and environmental data can permit environmentally conscious and cost-effective decision-making when driving a boat. To achieve this, we need to understand how best to integrate such data into boat dashboard interfaces. In this work, we design an Eco Dashboard inspired by eco-driving feedback dashboards in the automotive industry, as well as a variant of the Eco Dashboard that additionally visualizes historical route and fuel consumption data (Eco + Historical Dashboard). In an experimental simulation (N = 30) involving 12 experienced mariners and 18 novices, we compared both interfaces with a typical boat dashboard that presented fuel and speed. Our findings suggest that dashboards incorporating historical data, alongside eco-driving features, improve fuel efficiency and decision-making, particularly for non-experienced users. The Eco Dashboard supported real-time adjustments during complex navigation, whereas the Eco + Historical Dashboard enhanced route planning and confidence in longer-term decisions. Participants also reported greater confidence and reduced cognitive load when using these systems. These results provide valuable insights for the future design of maritime dashboard systems, offering a pathway to more effective and environmentally conscious navigation tools.},
keywords = {behaviour change, climate, dashboard, geospatial analytics, mobile, navigation, peripheral vision, simulation, training, virtual environment, visualization, wayfinding},
pubstate = {published},
tppubtype = {mastersthesis}
}
2024
Sathaporn "Hubert" Hu; Muhammad Raza; Derek Reilly
Gander: Preliminary Design and Evaluation of an AR + Tablet System for Geospatial Analysis Proceedings Article
In: IEEE Symposium on Mixed and Augmented Reality (ISMAR 2024) Adjunct Proceedings (MASK 2024), IEEE, 2024.
Links | BibTeX | Tags: AR, ARTIV, augmented reality, design, geospatial analytics, immersive visualization, visualization
@inproceedings{Hu2024b,
title = {Gander: Preliminary Design and Evaluation of an AR + Tablet System for Geospatial Analysis},
author = {Sathaporn "Hubert" Hu and Muhammad Raza and Derek Reilly},
url = {https://doi.org/10.1109/ISMAR-Adjunct64951.2024.00059},
doi = {10.1109/ISMAR-Adjunct64951.2024.00059},
year = {2024},
date = {2024-10-22},
urldate = {2024-10-22},
booktitle = {IEEE Symposium on Mixed and Augmented Reality (ISMAR 2024) Adjunct Proceedings (MASK 2024)},
publisher = {IEEE},
keywords = {AR, ARTIV, augmented reality, design, geospatial analytics, immersive visualization, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Francisco Bravo; Joana Amorim; Melika Besharati; Peter Bodorik; Vitor Cerqueira; Nuno Gomes; Jennie Korus; Mariana Oliveira; João Pimentel; Derek Reilly; Tyler Sclodnick; Jon Grant; Ramón Filgueira; Christopher Whidden; Luis Torgo
Advancing Precision Aquaculture Through Big Data Analytics and Machine Learning in Canadian Fish Farming Proceedings Article
In: OCEANS 2024, IEEE 2024.
Links | BibTeX | Tags: geospatial analytics, machine learning, statistics, visualization
@inproceedings{Bravo2024,
title = {Advancing Precision Aquaculture Through Big Data Analytics and Machine Learning in Canadian Fish Farming},
author = {Francisco Bravo and Joana Amorim and Melika Besharati and Peter Bodorik and Vitor Cerqueira and Nuno Gomes and Jennie Korus and Mariana Oliveira and João Pimentel and Derek Reilly and Tyler Sclodnick and Jon Grant and Ramón Filgueira and Christopher Whidden and Luis Torgo},
url = {10.1109/OCEANS55160.2024.10754571},
doi = {https://doi.org/10.1109/OCEANS55160.2024.10754571},
year = {2024},
date = {2024-09-24},
urldate = {2024-09-24},
booktitle = {OCEANS 2024},
organization = {IEEE},
keywords = {geospatial analytics, machine learning, statistics, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}