  In this paper, we examine a multi-sensor system where each sensor may monitor
more than one time-varying information process and send status updates to a
remote monitor over a common channel. We consider that each sensor's status
update may contain information about more than one information process in the
system subject to the system's constraints. To investigate the impact of this
correlation on the overall system's performance, we conduct an analysis of both
the average Age of Information (AoI) and source state estimation error at the
monitor. Building upon this analysis, we subsequently explore the impact of the
packet arrivals, correlation probabilities, and rate of processes' state change
on the system's performance. Next, we consider the case where sensors have
limited sensing abilities and distribute a portion of their sensing abilities
across the different processes. We optimize this distribution to minimize the
total AoI of the system. Interestingly, we show that monitoring multiple
processes from a single source may not always be beneficial. Our results also
reveal that the optimal sensing distribution for diverse arrival rates may
exhibit a rapid regime switch, rather than smooth transitions, after crossing
critical system values. This highlights the importance of identifying these
critical thresholds to ensure effective system performance.
