  Real-time safety assessment (RTSA) of dynamic systems is a critical task that
has significant implications for various fields such as industrial and
transportation applications, especially in non-stationary environments.
However, the absence of a comprehensive review of real-time safety assessment
methods in non-stationary environments impedes the progress and refinement of
related methods. In this paper, a review of methods and techniques for RTSA
tasks in non-stationary environments is provided. Specifically, the background
and significance of RTSA approaches in non-stationary environments are firstly
highlighted. We then present a problem description that covers the definition,
classification, and main challenges. We review recent developments in related
technologies such as online active learning, online semi-supervised learning,
online transfer learning, and online anomaly detection. Finally, we discuss
future outlooks and potential directions for further research. Our review aims
to provide a comprehensive and up-to-date overview of real-time safety
assessment methods in non-stationary environments, which can serve as a
valuable resource for researchers and practitioners in this field.
