  In many forest fire incidences, late detection of the fire has lead to severe
damages to the forest and human property requiring more resources to gain
control over the fire. An early warning and immediate response system can be a
promising solution to avoid such massive losses. This paper considers a network
consisting of multiple wireless sensors randomly deployed throughout the forest
for early prompt detection of fire. We present a framework to model fire
propagation in a forest and analyze the performance of considered wireless
sensor network in terms of fire detection probability. In particular, this
paper models sensor deployment as a Poisson point process (PPP) and models the
forest fire as a dynamic event which expands with time. We also present various
insights to the system including required sensor density and impact of wind
velocity on the detection performance. We show that larger wind velocity may
not necessarily imply bad sensing performance or the requirement of a denser
deployment.
