Presentation Information
[X5rLbKi3-06]Towards a Digital Twin for Search and Rescue Operations to Enhance Shipping Safety in the Canadian Arctic
*Floris Goerlandt1 (1. Dalhousie University (Canada))
Digital Twins of the Ocean (DTOs) increasingly provide integrated representations of oceanographic, sea-ice, and atmospheric conditions to support monitoring, forecasting, and decision-making. While these platforms offer detailed environmental intelligence, they currently provide only limited insight into the operational implications of those conditions for maritime safety and emergency response. This presentation outlines a vision and modeling progress for extending Digital Twin Ocean capabilities towards a Digital Twin for Search and Rescue (SAR) operations in the Canadian Arctic.
The proposed framework couples environmental information from ocean, sea-ice, and weather models with operational simulation models that estimate SAR system performance. Building on recent work towards understanding Maximum Expected Time to Rescue (METR) in the Canadian Arctic, the framework integrates probabilistic models of maritime and helicopter response operations that account for vessel availability, ice conditions, weather, asset capabilities, and operational constraints. These models estimate spatially and temporally varying response times across the Canadian Arctic, providing a dynamic representation of SAR capability rather than environmental conditions alone.
Within a Digital Twin architecture, these models form an operational layer that continuously interprets evolving environmental conditions in terms of expected emergency response performance. Such a system would support strategic preparedness, risk-informed voyage planning. Beyond monitoring current conditions, the framework enables predictive analyses that translate environmental forecasts into actionable estimates of rescue capability.
The presentation discusses the proposed Digital Twin architecture, the underlying modelling components, and the research challenges associated with integrating heterogeneous environmental and operational models into an adaptive decision-support capability for improving shipping safety in the Canadian Arctic.
The proposed framework couples environmental information from ocean, sea-ice, and weather models with operational simulation models that estimate SAR system performance. Building on recent work towards understanding Maximum Expected Time to Rescue (METR) in the Canadian Arctic, the framework integrates probabilistic models of maritime and helicopter response operations that account for vessel availability, ice conditions, weather, asset capabilities, and operational constraints. These models estimate spatially and temporally varying response times across the Canadian Arctic, providing a dynamic representation of SAR capability rather than environmental conditions alone.
Within a Digital Twin architecture, these models form an operational layer that continuously interprets evolving environmental conditions in terms of expected emergency response performance. Such a system would support strategic preparedness, risk-informed voyage planning. Beyond monitoring current conditions, the framework enables predictive analyses that translate environmental forecasts into actionable estimates of rescue capability.
The presentation discusses the proposed Digital Twin architecture, the underlying modelling components, and the research challenges associated with integrating heterogeneous environmental and operational models into an adaptive decision-support capability for improving shipping safety in the Canadian Arctic.
Comment
To browse or post comments, you must log in.Log in