Condition-based maintenance (CBM) detects early signs of failure and dictates when
maintenance should be performed based on the actual condition of a system. In this paper …

The Internet of Things (IoT) is on the verge of a major paradigm shift. In the IoT system of the
future, IoFT, the “cloud” will be substituted by the “crowd” where model training is brought to …

The feasibility of reliably generating bioenergy from forest biomass waste is intimately linked
to supply chain and production processing costs. These costs are, at least in part, directly …

Nonparametric degradation modeling can automatically formulate the principal degradation
pattern of condition monitoring signals. It performs higher flexibility than parametric modeling …

In this paper, we tackle a significant challenge in PCA: heterogeneity. When data are
collected from different sources with heterogeneous trends while still sharing some …

We introduce a relevant yet challenging problem named Personalized Dictionary Learning
(PerDL), where the goal is to learn sparse linear representations from heterogeneous …

Over the years, Internet of Things (IoT) devices have become more powerful. This sets forth
a unique opportunity to exploit local computing resources to distribute model learning and …

Revolutionary advances in Internet of Things technologies have paved the way for a
significant increase in computational resources at edge devices that collect condition …

The accurate and reliable prediction of remaining useful life (RUL) plays a crucial role in
ensuring the safe operation of batteries. Most existing RUL prediction methods are based on …

We present a nonparametric prognostic framework for individualized event prediction based
on joint modeling of both time series and time-to-event data. Our approach exploits a …