  Ecosystem of a forest suffers from many adverse events such as wild-fire
which can occur randomly anywhere in the forest and grows in size with time.
This paper aims to analyze performance of a network of randomly deployed
wireless sensors for the early detection of these time-critical and
time-evolving events in a forest. We consider that the forest lies in a
confined space (e.g. a circular region) and the wireless sensors, with fixed
sensing range, are deployed within the boundary of forest itself. The sensing
area of the network is modeled as a finite Boolean-Poisson model. In this
model, the locations of sensors are modeled as a finite homogeneous Poisson
Point Process (PPP) and the sensing area of each sensor is assumed to be a
finite set. This paper aims to answer questions about the proximity of a
typical sensor from a randomly occurred event and the total sensing area
covered by sensors. We first derive the distribution of contact distance of a
FHPPP and the expression of the capacity functional of a finite Boolean-Poisson
model. Using these, we then derive the probability of sensing the event at time
t, termed event-sensing probability.
