Transport Canada's Cargo Vessel Forecasting System is a machine learning pilot project developed in collaboration with the Port of Vancouver in 2024. This system analyzes historical cargo vessel registry data to predict when ships will arrive at port, helping port operators and government employees better plan and coordinate port operations.
The system uses aggregate data from the Port of Vancouver's vessel registry—no personal information about individuals is collected or processed. By improving visibility into vessel arrival patterns, the forecasting system supports more efficient operational planning and resource allocation. This is a retired pilot project that demonstrated the potential of machine learning for maritime logistics optimization.
Key facts: This system does not involve personal information collection. Primary users are Government of Canada employees. The project is retired but demonstrated valuable insights for future maritime planning initiatives.
