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024 7 _a10.1007/978-3-031-39619-9
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050 4 _aTK5105.8857
072 7 _aUT
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072 7 _aCOM043000
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245 1 0 _aInternational Congress and Workshop on Industrial AI and eMaintenance 2023
_h[electronic resource] /
_cedited by Uday Kumar, Ramin Karim, Diego Galar, Ravdeep Kour.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXII, 801 p. 351 illus., 287 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
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338 _aonline resource
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347 _atext file
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490 1 _aLecture Notes in Mechanical Engineering,
_x2195-4364
505 0 _aUse cases of Generative AI in Asset Management of Railways -- A neuroergonomics mirror-based platform to enhance cognitive impairments in fighter pilots -- Risk-based safety improvements in railway asset management -- Performance of Reinforcement Learning in Molecular Dynamics Simulations: A Case Study of Hydrocarbon Dynamics -- Causal Effects of Railway Track Maintenance – An Experimental Case Study of Tamping -- Self-Driving Cars in the Arctic Environment -- Towards a Railway Infrastructure Digital Twin Framework for African Railway Lifecycle Management.
520 _aThis proceedings brings together the papers presented at the International Congress and Workshop on Industrial AI and eMaintenance 2023 (IAI2023). The conference integrates the themes and topics of three conferences: Industrial AI & eMaintenance, Condition Monitoring and Diagnostic Engineering Management (COMADEM) and, Advances in Reliability, Maintainability and Supportability (ARMS) on a single platform. This proceedings serves both academy and industry in providing an excellent platform for collaboration by providing a forum for exchange of ideas and networking. The 21st century has seen remarkable progress in Artificial Intelligence, with application to a variety of fields (computer vision, automatic translation, sentiment analysis in social networks, robotics, etc.) The IAI2023 focuses on Industrial Artificial Intelligence, or IAI. The emergence of industrial AI applications holds tremendous promises in terms of achieving excellence and cost-effectiveness in the operation and maintenance of industrial assets. Opportunities in Industrial AI exist in many industries such as aerospace, railways, mining, construction, process industry, etc. Its development is powered by several trends: the Internet of Things (IoT); the increasing convergence between OT (operational technologies) and IT (information technologies); last but not least, the unabated fast-paced developments of advanced analytics. However, numerous technical and organizational challenges to the widespread development of industrial AI still exist. The IAI2023 conference and its proceedings foster fruitful discussions between AI creators and industrial practitioners.
650 0 _aInternet of things.
_958845
650 0 _aCooperating objects (Computer systems).
_964303
650 0 _aArtificial intelligence.
_958441
650 0 _aIndustrial engineering.
650 0 _aProduction engineering.
650 1 4 _aInternet of Things.
_958845
650 2 4 _aCyber-Physical Systems.
_965638
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aIndustrial and Production Engineering.
700 1 _aKumar, Uday.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aKarim, Ramin.
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_4http://id.loc.gov/vocabulary/relators/edt
_968712
700 1 _aGalar, Diego.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_968713
700 1 _aKour, Ravdeep.
_eeditor.
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031396182
776 0 8 _iPrinted edition:
_z9783031396205
830 0 _aLecture Notes in Mechanical Engineering,
_x2195-4364
856 4 0 _uhttps://doi.org/10.1007/978-3-031-39619-9
912 _aZDB-2-ENG
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