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}
}
Rowland Goddy-Worlu; James Forren; Claire Nicholas; Martha Dais Ferreira; Derek Reilly
Preserving Intangible Cultural Heritage through Augmented Reality and Machine Learning: A Case Study of the One-bead Netting Stitch Journal Article Forthcoming
In: ACM Journal on Computing and Cultural Heritage, Forthcoming.
BibTeX | Tags: architecture, augmented reality, craft, cultural heritage, gesture, immersive visualization, machine learning, mixed reality, natural user interface, training
@article{nokey,
title = {Preserving Intangible Cultural Heritage through Augmented Reality and Machine Learning: A Case Study of the One-bead Netting Stitch},
author = {Rowland Goddy-Worlu and James Forren and Claire Nicholas and Martha Dais Ferreira and Derek Reilly},
year = {2026},
date = {2026-05-31},
journal = {ACM Journal on Computing and Cultural Heritage},
keywords = {architecture, augmented reality, craft, cultural heritage, gesture, immersive visualization, machine learning, mixed reality, natural user interface, training},
pubstate = {forthcoming},
tppubtype = {article}
}
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}
}
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.
2023
Peter Haltner; Rowland Goddy-Worlu; Claire Nicholas; James Forren; Derek Reilly
A Comparative Evaluation of AR Embodiments vs. Videos and Figures for Learning Bead Weaving Conference
Proceedings of the 22nd IEEE International Symposium on Mixed and Augmented Reality (ISMAR), IEEE, 2023.
Abstract | Links | BibTeX | Tags: AR, augmented reality, craft, cultural heritage, embodied interaction, training
@conference{nokey,
title = {A Comparative Evaluation of AR Embodiments vs. Videos and Figures for Learning Bead Weaving},
author = {Peter Haltner and Rowland Goddy-Worlu and Claire Nicholas and James Forren and Derek Reilly},
url = {https://doi.org/10.1109/ISMAR59233.2023.00136},
doi = {10.1109/ISMAR59233.2023.00136},
year = {2023},
date = {2023-10-16},
urldate = {2023-10-16},
booktitle = {Proceedings of the 22nd IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
publisher = {IEEE},
abstract = {The most common learning materials for handcraft today are videos and figures, which are limited in their ability to express embodied knowledge as an in-person tutor could. We developed WeavAR, an application for headworn augmented reality (AR) displays designed to teach basic bead weaving patterns. WeavAR combines virtual 3D hands showing weaving sequences recorded from an experienced bead weaver and a dynamic 3D bead model showing how the work progresses. Using a mixed within/between-subjects user study (n=30), we compared learning materials (AR to videos and figures) and learning material placement (in the area of work or to the side). Results show that the AR learning materials had comparable effectiveness to video and figures. Hand visualizations were found to lack crucial context, however, making them less useful than the 3D bead model. Extra measures to prevent obstruction are required when placing learning materials at the area of work.},
keywords = {AR, augmented reality, craft, cultural heritage, embodied interaction, training},
pubstate = {published},
tppubtype = {conference}
}
The most common learning materials for handcraft today are videos and figures, which are limited in their ability to express embodied knowledge as an in-person tutor could. We developed WeavAR, an application for headworn augmented reality (AR) displays designed to teach basic bead weaving patterns. WeavAR combines virtual 3D hands showing weaving sequences recorded from an experienced bead weaver and a dynamic 3D bead model showing how the work progresses. Using a mixed within/between-subjects user study (n=30), we compared learning materials (AR to videos and figures) and learning material placement (in the area of work or to the side). Results show that the AR learning materials had comparable effectiveness to video and figures. Hand visualizations were found to lack crucial context, however, making them less useful than the 3D bead model. Extra measures to prevent obstruction are required when placing learning materials at the area of work.