AI RESEARCH
On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems
arXiv CS.AI
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ArXi:2605.07860v1 Announce Type: cross Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT) environments. While discriminative models dominate most FL use cases, recent advances in generative models -- such as Variational Autoencoders (VAE), Generative Adversarial Networks (GAN), and Diffusion Models (DM) -- offer new opportunities for unsupervised anomaly detection in time series analysis, with relevant applications in predictive maintenance (PdM) in critical industrial infrastructures.