&lt;b&gt;Recent Research and Development Activities in Maintenance Technologies for Electric Railway Power Supply Systems&lt;/b&gt;

Ikeda, Mitsuru

doi:10.2219/rtriqr.61.1_6

Cited by 9 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By leveraging IoT-generated data to build digital twins, railway companies can optimize their operations, minimize downtime, and enhance safety and security through CBM [71]. For example, in the context of predictive upkeep that serves the SIA H2020 project, [72] proposed an IoT data collection approach to support DT creation.…”

Section: Dt Technologymentioning

confidence: 99%

Digital Twin for Railway: A Comprehensive Survey

Ghaboura,

Ferdousi,

Laamarti

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Digital transformation has been prioritized in the railway industry to bring automation to railway operations. Digital Twin (DT) technology has recently gained attention in the railway industry to fulfill this goal. Contemporary researchers argue that DT can be advantageous in Railway manufacturing logistics to planning and scheduling. Although underlying technologies of DT, e.g., modelling, computer vision, and the Internet of Things, have been studied for various railway industry applications, the DT has been least explored in the context of railways. Thus, in this paper, we aim to understand the state-of-the-art of DT for railway (DTR), for advanced railway systems. Besides, this survey clarifies how DT can serve the railway twin system designers and developers. As DTR is still in its early adoption stage, there is hardly any clear direction to identify the technologies for specific DTR applications. Therefore, based on our findings we present a taxonomy for DTR for designers and developers. Finally, we describe potential challenges, pitfalls, and opportunities in DTR for future researchers.

show abstract

Section: Dt Technologymentioning

confidence: 99%

Digital Twin for Railway: A Comprehensive Survey

Ghaboura,

Ferdousi,

Laamarti

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

Railway Digital Twins and Artificial Intelligence: Challenges and Design Guidelines

Dirnfeld

Donato

Flammini

et al. 2022

Communications in Computer and Information Science

View full text Add to dashboard Cite

In the last years, there has been a growing interest in the emerging concept of Digital Twins (DTs) among soJware engineers and researchers. DTs represent a promising paradigm to enhance the predictability, safety, and reliability of cyber-physical systems. They can play a key role in different domains, as it is also witnessed by several ongoing standardisa2on ac2vi2es. However, several challenging issues have to be faced in order to effec2vely adopt DTs, in par2cular when dealing with cri2cal systems. This work provides a review of the scien2fic literature on DTs in the railway sector, with a special focus on their rela2onship with Ar2ficial Intelligence. Challenges and opportuni2es for the usage of DTs in railways have been iden2fied, with interoperability being the most discussed challenge. One difficulty is to transmit opera2onal data in real-2me from edge systems to the cloud in order to achieve 2mely decision making. We also provide some guidelines to support the design of DTs with a focus on machine learning for railway maintenance.

show abstract

Towards AI-assisted digital twins for smart railways: preliminary guideline and reference architecture

Donato

Dirnfeld

Somma

et al. 2023

J Reliable Intell Environ

View full text Add to dashboard Cite

In the last years, there has been a growing interest in the emerging concept of digital twins (DTs) among software engineers and researchers. DTs not only represent a promising paradigm to improve product quality and optimize production processes, but they also may help enhance the predictability and resilience of cyber-physical systems operating in critical contexts. In this work, we investigate the adoption of DTs in the railway sector, focusing in particular on the role of artificial intelligence (AI) technologies as key enablers for building added-value services and applications related to smart decision-making. In this paper, in particular, we address predictive maintenance which represents one of the most promising services benefiting from the combination of DT and AI. To cope with the lack of mature DT development methodologies and standardized frameworks, we detail a workflow for DT design and development specifically tailored to a predictive maintenance scenario and propose a high-level architecture for AI-enabled DTs supporting such workflow.

show abstract

<b>Recent Research and Development Activities in Maintenance Technologies for Electric Railway Power Supply Systems</b>

Cited by 9 publications

References 5 publications

Digital Twin for Railway: A Comprehensive Survey

Digital Twin for Railway: A Comprehensive Survey

Railway Digital Twins and Artificial Intelligence: Challenges and Design Guidelines

Towards AI-assisted digital twins for smart railways: preliminary guideline and reference architecture

Contact Info

Product

Resources

About