Railway Infrastructure Monitoring Framework (RIMF) for Hudson Bay Railway
- Language of the publication
- English
- Date
- 2024-02-11
- Type
- Consultant report
- Author(s)
- Oliver Wang
- Publisher
- Hudson Bay Railway
Alternative title
Cadre de surveillance de l’infrastructure ferroviaire pour les chemins de fer de la Baie-d’Hudson
Abstract
Railway networks are essential for transportation and supply chains in northern communities, yet they face growing challenges from extreme weather conditions, permafrost thaw, and aging infrastructure. This project addresses these challenges through the development and deployment of the Railway Infrastructure Monitoring Framework (RIMF), an innovative solution by a Canadian technology developer and Hudson Bay railway. The RIMF integrates advanced AI/ML algorithms, Interferometric Synthetic Aperture Radar (InSAR) satellite imagery, underground mapping, LiDAR, climate models, and hardware rail track monitoring units (ATMU) to monitor track conditions, detect deformations, and predict risks. Key milestones include the deployment of ATMU prototypes, extensive data collection, InSAR-based deformation analysis, customized climate modeling, and the development of a user-friendly dashboard and reporting system. Initial results demonstrate RIMF's potential to reduce reliance on manual inspections, enhance predictive maintenance, and mitigate the impact of weather events on regional railways.
Description
This report outlines the development, testing, and application of the Railway Infrastructure Monitoring Framework (RIMF), an Artificial Intelligence (AI) driven system designed to enhance railway infrastructure monitoring. It highlights how RIMF integrates climate modeling, satellite imagery (including Interferometric Synthetic Aperture Radar (InSAR)), and real-time environmental and track data to provide a technological solution for analyzing infrastructure deformation, underground mapping, and track geometry to improve the safety, efficiency, and sustainability of rail-based transit systems.
Subject
- Rail transport,
- Railway safety,
- Climate change
Keywords
- Rail,
- Transportation,
- InSAR-Interferometric Synthetic Aperture Radar,
- LiDAR-Laser imaging Detection and Ranging,
- permafrost,
- thaw,
- climate change,
- Cold weather,
- AI-Artificial intelligence,
- GPR-Ground Penetrating Radar,
- Condition monitoring,
- Framework,
- Climate models,
- Predictive maintenance
Rights
Pagination
1-21
Peer review
Yes
Identifiers
- Government document number
- 1TJC06XY54SB-1102879366-1954
- Organization
- RCCAP-2024-033101
Citation(s)
Wang, O. (2024). Railway Infrastructure Monitoring Framework (RIMF) for Hudson Bay Railway. ApoSys Technologies Inc.