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

On Detection of Critical Events in a Finite Forest using Randomly Deployed Wireless Sensors