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E-raamat: International Congress and Workshop on Industrial AI and eMaintenance 2025

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International Congress and Workshop on Industrial AI and eMaintenance 2025Suurem pilt
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This proceedings volume will document the state-of-the-art research, case studies, and technological advancements in Industrial Artificial Intelligence and intelligent asset management. The content will be relevant to industrial and academic audiences, covering topics such as eMaintenance, Industry 5.0, predictive analytics, intelligent asset management, cybersecurity, and advanced digitalisation solutions. By presenting both academic and practical insights, the volume aims to bridge the gap between theory and application in managing industrial assets. The primary readership includes professionals, researchers, and students interested in the applications of AI for optimizing industrial operations and maintenance.

A Performability Optimization Framework for Driverless and Unattended
Mainline Systems.- Deep Reinforcement Learning for Maintenance Planning in
Weibull Distributed Fleet Systems.- Synthetic MQTT Traffic Generation for
Real-Time IoT Security Threat Analysis with Artificial Intelligence.-
Balancing Cost, Risk, and Performance in Railway Asset Management: An
Enhanced ORIE Approach.- Effective Gravel Road Maintenance: Insights from
Condition Assessment by Integrating Data Sources.- Fundamentals of RCM and
their application in railway infrastructure asset management.- On the
development and use of hybrid models in aircraft component and sub-system
health monitoring.- Development of fault diagnostic support Application for
railway sleepers.- Design and Prognosis of CanSat Maneuver Systems using
Machine Learning.- Review of Neuroergonomics approaches for evaluating mental
workload.- Making correct maintenance decisions - A content analysis of
Reliability-Centered Maintenance (RCM).- Life Cycle Management of Railway
Infrastructure - A Case Study at the Swedish Iron Ore Line.- A Generative AI
Framework for Smart Maintenance: Utilizing RAG Systems and LLMs to Assist
Manufacturing Operations.- Data-driven decision support tool for maintenance
of capital-intensive mining equipment.- Enhancing Railway Infrastructure
Resilience: Towards A Hybrid Multi-physics and Data-Driven Approach for
Condition Monitoring.- European Union Data act enabling IoT data sharing for
creation of new services and software products.- EEG Signal Analysis in Golf
Putting: Correlating Brain Activity with Putting Success.- Support for daily
decisions of safety on scaffolding at construction sites through applied AI.-
Using Data from Multiple Wayside Train Monitoring Systems to Detect and
Estimate the Size of Wheel Flats on Railway Vehicles.
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Püsilink: https://www.kriso.ee/db/97830320372512e.html