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Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

University of Ottawa

$299,750.00

Development of an AI application for a health monitoring system for condition-based maintenance applied to rail infrastructure

FY 2020-21 · 2021-03-31

Summary
In order to reduce the risks of failure in rail infrastructure, a more advanced systematic health monitoring approach based on artificial intelligence methods is being researched. This Project aims to develop an AI-based tool to improve the health monitoring systems associated with rail infrastructure. This new tool will be able to provide long term and short-term prediction of the rail temperature as a key component for rail infrastructure safety, and the new tool will be based on artificial intelligence approaches that combine the observational historical data on climatic and weather conditions with computer techniques. The tool can be fed with long-term and short-term projections of climatic condition to provide insight into the rail temperature changes and its implications for rail infrastructure safety.
Program
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Location
Ottawa|Ottawa, Ontario, Canada
Recipient Type
Academia
Business Number
119278877
Type
Grant
Source
Proactive Disclosure - Grants and Contributions

As published

Agreement End Date
2024-03-31
Agreement Number
969095
Agreement Start Date
2021-03-31
Agreement Title
Development of an AI application for a health monitoring system for condition-based maintenance applied to rail infrastructure
Agreement Title (French)
Élaboration d’une application axée sur l’IA pour surveiller l’état des infrastructures ferroviaires dans le cadre d’un entretien préventif des voies ferrées
Agreement Type
Grant
Agreement Value
$299,750.00
Amendment Number
0
Description
In order to reduce the risks of failure in rail infrastructure, a more advanced systematic health monitoring approach based on artificial intelligence methods is being researched. This Project aims to develop an AI-based tool to improve the health monitoring systems associated with rail infrastructure. This new tool will be able to provide long term and short-term prediction of the rail temperature as a key component for rail infrastructure safety, and the new tool will be based on artificial intelligence approaches that combine the observational historical data on climatic and weather conditions with computer techniques. The tool can be fed with long-term and short-term projections of climatic condition to provide insight into the rail temperature changes and its implications for rail infrastructure safety.
Description (French)
Les recherches portent sur l’élaboration d’une approche méthodique plus poussée à la surveillance de l’état des infrastructures ferroviaires qui fera appel à l’intelligence artificielle afin d’atténuer le risque que de telles infrastructures défaillent. Le projet verra le développement d’un outil axé sur l’IA qui améliorera les systèmes qui surveillent l’état des ouvrages ferroviaires. Le nouvel outil produira des prévisions à court et à long terme sur la température des rails, paramètre crucial pour la sécurité des voies ferrées. Il recourra pour cela à l’intelligence artificielle, en combinant les observations historiques sur les conditions climatiques et météorologiques aux techniques informatiques. On pourra l’alimenter avec des projections à court et à long terme des conditions climatiques de manière à avoir une idée de la variation de la température des rails et de ses répercussions sur la sûreté des ouvrages ferroviaires.
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
Ottawa–Vanier
Federal Riding (French)
Ottawa–Vanier
Federal Riding Number
35078
NAICS Code
541710 - R&D in the physical, engineering and life sciences
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
Program Purpose
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
119278877
Recipient City
Ottawa|Ottawa
Recipient Country
CA
Recipient Legal Name
University of Ottawa
Recipient Postal Code
K1N 6N5
Recipient Province or Territory
ON
Recipient Type
S
Reference Number
172-2020-2021-Q4-969095
University of Ottawa - $299,750 Grant (2020-21) | Canada Spends