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A Review of Intelligent Infrastructure Surveillance to Support Safe Autonomy in Smart-Railways
Uppsala University, Uppsala, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Linnaeus University, Växjö, Sweden; University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland.ORCID iD: 0000-0002-2833-7196
2023 (English)In: IEEE Conf Intell Transport Syst Proc ITSC, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 5603-5610Conference paper, Published paper (Refereed)
Abstract [en]

Since railways are considered among the most critical transportation infrastructures, significant research exists on the use of modern technology for their safety and security. In order to enable full autonomy of railway operations, it is not only important to guarantee safety from the control system perspective, but also to ensure that external threats of both intentional and natural origin are detected automatically. This literature review highlights the potential of Artificial Intelligence (AI) in physical infrastructure security and surveillance of autonomous railway operations. We survey AI applications to identify unauthorized access to restricted areas, as well as intelligent monitoring against natural disasters. We also discuss the use of AI to improve situational awareness, in order to analyze data from various sources to prevent incidents, provide real-time information to decision-makers, and support emergency response. Finally, we highlight the challenges to overcome, including data quality, privacy concerns, regulations, and other technical limitations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2023. p. 5603-5610
Keywords [en]
Disaster prevention, Disasters, Railroads, Area monitoring, Infrastructure security, Intelligent infrastructures, Literature reviews, Modern technologies, Railway operations, Safety and securities, Security and surveillances, Transportation infrastructures, Unauthorized access, Decision making
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-66242DOI: 10.1109/ITSC57777.2023.10422317ISI: 001178996705098Scopus ID: 2-s2.0-85186497675ISBN: 9798350399462 (print)OAI: oai:DiVA.org:mdh-66242DiVA, id: diva2:1845533
Conference
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Available from: 2024-03-19 Created: 2024-03-19 Last updated: 2024-06-19Bibliographically approved

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Flammini, Francesco

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf