Deep Learning for Proactive Vehicle Maintenance

Explore the evolution of vehicle diagnostics through an introduction to predictive maintenance, addressing limitations of fault-code-based systems and challenges in modeling non-stationary data. Learn about the ProActiveCar-DI framework, aiming for 85% accurate degradation detection, leveraging Bayesian methods, and delivering actionable maintenance recommendations. This research establishes robust automotive datasets, tackles integration gaps in predictive platforms, and develops tools for...