St. Lawrence Seaway’s journey into PI System with advanced analytics for vessel ETA forecasting at bridges and locks

2024 - AVEVA World - Paris - Infrastructure (Water, Facilities, Transport, Marine, DC)

St. Lawrence Seaway's journey into PI System with advanced analytics for vessel ETA forecasting at bridges and locks

St. Lawrence Seaway operates the bridges and locks along the St. Lawrence Seaway system. Our original ETAs where based on historic standard transit time as a way to have an idea (rough estimate) of when vessels would reach bridges and locks. These times where not very accurate due to a number of reasons, however, they were meant only for internal use. As cities have grown around the system the volume of traffic crossing the movable bridges has significantly increased and there became a need to provide this information to the public. In the next generation, the bridge status estimated times were being calculated by a few different systems using different calculation methods depending on the bridge location and surrounding environment. Some bridges are located along a stretch of the Seaway unencumbered by locks or other physical impediments, while others are situated right next to locks. Depending on a vessel's approach to a bridge, the estimated times need to be calculated differently. It became clear that these methods were not good enough. There were many elements in which the St. Lawrence Seaway did not have control over and they realized more advance analysis and AI was needed to help get better ETA. As a Premier Partner of AVEVA, Maya HTT has over 12 years of experience implementing and integrating the PI System at customers across various industries from Transportation and Marine to Datacenters and Manufacturing and Oil&Gas; St-Lawrence Seaway selected Maya HTT to accelerate their journey into advanced analytics leveraging the PI System data and external data sources. This topic details our journey evolving from the early days of using historic standards to today using AIS, SCADA, and historical data to build models in PI Asset Framework using PI Asset Analyitcs and machine learning to come up with better predictions.

Industry

Marine

Company

St. Lawrence Seaway Management Corporation

Speaker

Jamie Andrews

Jamie has 25+ years of experience working in both the Pulp and Paper and the Marine Transportation industries. Through his career in Information Technology and Systems he has touch almost every facet of business, improving processes and implementing new systems. In his current role at the St. Lawrence Seaway Jamie is leading the Information Systems team to bring change in how we capture and manage data, to modernize our systems and to how we can use AI for improving our business outcomes.

Company

May aHTT

Speaker

Remi Duquette

With 20+ years of experience building practical, effective solutions, Remi now plays a key role in heading Maya HTT's industrial IoT, edge, and AI business. He is a sought-after guest speaker with dozens of successful industrial AI/ML/simulation projects to his credit. From his achievement as a young short-track speed skating champion, to his instrumental contributions to successful industrial AI-operations deployments, to the structural design and analysis of five spacecraft currently in orbit, when it comes to "mission-critical", Remi is an asset to all Maya HTT clients.

Session Code

AW24-INF-D2-SESS-168