  Timely status updating is crucial for future applications that involve remote
monitoring and control, such as autonomous driving and Industrial Internet of
Things (IIoT). Age of Information (AoI) has been proposed to measure the
freshness of status updates. However, it is incapable of capturing critical
systematic context information that indicates the time-varying importance of
status information, and the dynamic evolution of status. In this paper, we
propose a context-based metric, namely the Urgency of Information (UoI), to
evaluate the timeliness of status updates. Compared to AoI, the new metric
incorporates both time-varying context information and dynamic status
evolution, which enables the analysis on context-based adaptive status update
schemes, as well as more effective remote monitoring and control. The
minimization of average UoI for a status update terminal with an updating
frequency constraint is investigated, and an update-index-based adaptive scheme
is proposed. Simulation results show that the proposed scheme achieves a
near-optimal performance with a low computational complexity.
