In this paper, we propose a novel 3D sensing model for the sensor placement optimization problem given a three dimensional environment. The model take into account the angles of a sensor, the distance between the sensor and a given point in the terrain, the Line-of-Sight (visibility) capability, the constraints of the terrain and the number of sensors needed to maximize the coverage over the terrain. In order to generate optimal solutions to the model, we firstly present a novel Line-of-Sight (LoS) method aiming to determine the number of obstacles between a given sensor and a point in the region of interest using the ideas of adaptive lengths and linear regression. Secondly, we propose a modification of PSO algorithm, where particles (sensors) update their velocity by using only local information coming from their neighbors. The comparison and analyses of experimental results reveal that optimal solutions achieved from the 3D sensing model are better than those of the related work.

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