In this paper, we propose a graph-based method for distributed event-region detection in a wireless sensor
network (WSN). The proposed method is developed by exploiting the fact that the true events at geographically
neighboring sensors have a statistical dependency in an event-region detection scenario. This spatial dependence
amongst the sensors is modeled using graphical models (GMs) and serves as a regularization term to enhance the
detection accuracy. The method involves solving a linear system of equations, which can be readily implemented
in a distributed fashion. Numerical results are presented to illustrate the performance of our proposed approach.