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The problem treated in this paper is about optimal visual sensors placement and deployment with estimation of the appropriate location of an interceptor to be placed. The main objective of this research is to ensure accurate coverage of the monitoring space with a minimum number of directional “field-of-view” (FOV) cameras and in the same time to decrease the interception time of an intruder at any entry of a target traveling between two areas. Firstly, we define the coverage problem by realistic and consistent assumptions taking into account the capabilities and limits of the cameras. Then, a novel method based on Binary Particle Swarm Optimization (BPSO) and inspired probability is proposed for solving the cameras placement for coverage problem. The performances of the proposed approach are discussed and compared with several stochastic algorithms such as genetic algorithms, immune system and some adapted versions of evolutionary algorithms based on the BPSO. In the second part of the paper, we address an improved optimal polynomial time algorithm for computing the worst-case breach coverage in directional FOV sensor networks, which represent the best position of an interceptor to be placed.