  In this paper, we study the structural state and input observability of
continuous-time switched linear time-invariant systems and unknown inputs.
First, we provide necessary and sufficient conditions for their structural
state and input observability that can be efficiently verified in
$O((m(n+p))^2)$, where $n$ is the number of state variables, $p$ is the number
of unknown inputs, and $m$ is the number of modes. Moreover, we address the
minimum sensor placement problem for these systems by adopting a feed-forward
analysis and by providing an algorithm with a computational complexity of $
O((m(n+p)+\alpha)^{2.373})$, where $\alpha$ is the number of target strongly
connected components of the system's digraph representation. Lastly, we explore
different assumptions on both the system and unknown inputs (latent space)
dynamics that add more structure to the problem, and thereby, enable us to
render algorithms with lower computational complexity, which are suitable for
implementation in large-scale systems.
