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Integrating AI and ...
Integrating AI and DTs : challenges and opportunities in railway maintenance application and beyond
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- Dirnfeld, Ruth (författare)
- Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Linnaeus Univ, Dept Comp Sci & Media Technol, Växjö, Sweden.
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- De Donato, Lorenzo (författare)
- Univ Naples Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy.
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- Somma, Alessandra (författare)
- Univ Naples Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy.
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- Saman Azari, Mehdi (författare)
- Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Linnaeus Univ, Dept Comp Sci & Media Technol, Växjö, Sweden.
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- Marrone, Stefano (författare)
- Univ Naples Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy.
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- Flammini, Francesco, Senior Lecturer, 1978- (författare)
- Mälardalens universitet,Linnéuniversitetet,Institutionen för datavetenskap och medieteknik (DM),Mälardalen University, Sweden,Innovation och produktrealisering,Linnaeus Univ, Dept Comp Sci & Media Technol, Växjö, Sweden.
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- Vittorini, Valeria (författare)
- Univ Naples Federico II, Dept Elect Engn & Informat Technol, Via Claudio 21, I-80125 Naples, Italy.
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(creator_code:org_t)
- 2024
- 2024
- Engelska.
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Ingår i: Simulation (San Diego, Calif.). - : Sage Publications. - 0037-5497 .- 1741-3133.
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- In the last years, there has been a growing interest in the emerging concept of digital twin (DT) as it represents a promising paradigm to continuously monitor cyber-physical systems, as well as to test and validate predictability, safety, and reliability aspects. At the same time, artificial intelligence (AI) is exponentially affirming as an extremely powerful tool when it comes to modeling the behavior of physical assets allowing, de facto, the possibility of making predictions on their potential evolution. However, despite the fact that DTs and AI (and their combination) can act as game-changing technologies in different domains (including the railways), several challenges have to be faced to ensure their effectiveness, especially when dealing with safety-critical systems. This paper provides a narrative review of the scientific literature on DTs for railway maintenance applications, with a special focus on their relationship with AI. The aim is to discuss the opportunities the integration of these two technologies could open in railway maintenance applications (and beyond), while highlighting the main challenges that should be overcome for its effective implementation.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- Digital twin
- railway
- artificial intelligence
- machine learning
- cyber-physical system
- Internet of things
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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