04624nam a22006015i 4500 978-3-031-39619-9 DE-He213 20251030110904.0 cr nn 008mamaa 231130s2024 sz | s |||| 0|eng d 9783031396199 978-3-031-39619-9 10.1007/978-3-031-39619-9 doi TK5105.8857 UT bicssc COM043000 bisacsh UT thema International Congress and Workshop on Industrial AI and eMaintenance 2023 [electronic resource] / edited by Uday Kumar, Ramin Karim, Diego Galar, Ravdeep Kour. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XII, 801 p. 351 illus., 287 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes in Mechanical Engineering, 2195-4364 Use 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. This 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. Internet of things. 58845 Cooperating objects (Computer systems). 64303 Artificial intelligence. 58441 Industrial engineering. Production engineering. Internet of Things. 58845 Cyber-Physical Systems. 65638 Artificial Intelligence. 58441 Industrial and Production Engineering. Kumar, Uday. editor. edt http://id.loc.gov/vocabulary/relators/edt 68711 Karim, Ramin. editor. edt http://id.loc.gov/vocabulary/relators/edt 68712 Galar, Diego. editor. edt http://id.loc.gov/vocabulary/relators/edt 68713 Kour, Ravdeep. editor. edt http://id.loc.gov/vocabulary/relators/edt 68714 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031396182 Printed edition: 9783031396205 Lecture Notes in Mechanical Engineering, 2195-4364 https://doi.org/10.1007/978-3-031-39619-9 ZDB-2-ENG ZDB-2-SXE 56949 56949