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Grant: Collaborative Science, Technology and Innovation Program – Ideation Fund

Simon Fraser University

$231,000.00

Identification and characterization of vessel operational best practices using machine learning

FY 2021-22 · 2021-09-01

Summary
The Project involves the analysis of vessel operational data to identify and characterize operator best practices for navigating through a given route with optimal fuel performance. The Project is being conducted for a vessel that operates along a single transit route. Operational data from the vessel has already been collected for two consecutive years and will be used as the basis of this investigation. The analysis of the large data set will use machine learning techniques in an attempt to identify key features of the navigation technique that will lead to optimal fuel performance. These features will then be characterized and incorporated into a decision support system framework that will be used for this vessel and potentially vessels as well as fostering additional research.
Program
Collaborative Science, Technology and Innovation Program – Ideation Fund
Location
Burnaby|Burnaby, British Columbia, Canada
Recipient Type
Academia
Business Number
118520725
Type
Grant
Source
Proactive Disclosure - Grants and Contributions

As published

Additional Information
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 729 days.This agreement has been amended 1 time(s). The total amended value is $231,000.
Additional Information (French)
Cet accord a été modifié 1 fois. La date de fin du présent accord a été changé de 729 jours. This agreement has been amended 1 time(s). La valeur totale des modifications est de 231,000$. dollars.
Agreement End Date
2026-08-31
Agreement Number
975727
Agreement Start Date
2021-09-01
Agreement Title
Identification and characterization of vessel operational best practices using machine learning
Agreement Title (French)
Identification et caractérisation des meilleures pratiques d’exploitation des navires à l’aide de l’apprentissage automatique
Agreement Type
Grant
Agreement Value
$231,000.00
Amendment Date
2023-06-20
Amendment Number
1
Description
The Project involves the analysis of vessel operational data to identify and characterize operator best practices for navigating through a given route with optimal fuel performance. The Project is being conducted for a vessel that operates along a single transit route. Operational data from the vessel has already been collected for two consecutive years and will be used as the basis of this investigation. The analysis of the large data set will use machine learning techniques in an attempt to identify key features of the navigation technique that will lead to optimal fuel performance. These features will then be characterized and incorporated into a decision support system framework that will be used for this vessel and potentially vessels as well as fostering additional research.
Description (French)
Ce projet consiste à analyser les données d’exploitation des navires afin de recenser et de caractériser les meilleures pratiques de navigation le long d’un itinéraire donné, en maintenant une consommation optimale de carburant. Il est réalisé sur un navire exploité sur un itinéraire unique. Les données d’exploitation du navire ont déjà été recueillies sur deux années consécutives et serviront de point de départ à cette étude. Nous utiliserons des techniques d’apprentissage automatique pour analyser ce vaste ensemble de données et chercher ainsi à déterminer les caractéristiques principales de la technique de navigation conduisant à une consommation optimale de carburant. Ces informations seront ensuite intégrées dans un système d’aide à la prise de décisions et pourraient être utiles tant pour le navire en question que pour d’autres, tout en ouvrant la voie à de nouvelles recherches.
Expected Results
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
Burnaby North–Seymour
Federal Riding (French)
Burnaby-Nord–Seymour
Federal Riding Number
59002
NAICS Code
541710
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program – Ideation Fund
Program Name (French)
Programme de collaboration en science, en technologie et en innovation – Fonds d’idéation
Program Purpose
The Ideation Fund is intended to encourage, test and validate transformative research ideas generated by teams of NRC scientific personnel and external collaborators with complementary capabilities, acting as a demonstration phase for a continually-evolving suite of research and development (R&D) deliverables at the NRC. The fund supports exploratory research through two mechanisms: the New Beginnings Initiative and the Small Teams Initiative.
Program Purpose (French)
Le Fonds d’idéation vise à encourager, à mettre à l’essai et à valider les idées de recherche transformatrice des équipes scientifiques du CNRC et des collaborateurs externes dotés de capacités complémentaires. Il servira ainsi de plateforme de démonstration d’une série de produits livrables en matière de recherche-développement (R-D) en constante évolution au CNRC. Le Fonds appuie la recherche exploratoire au moyen de deux mécanismes : l’Initiative « Nouveaux débuts » et l’Initiative « Petites équipes ».
Recipient Business Number
118520725
Recipient City
Burnaby|Burnaby
Recipient Country
CA
Recipient Legal Name
Simon Fraser University
Recipient Postal Code
V5A 1S6
Recipient Province or Territory
BC
Recipient Type
S
Reference Number
172-2021-2022-Q1-975727