In optimal design of monitoring systems, maximizing the coverage and quality at a minimum cost, the proper positioning of cameras is an important issue and the quality of the image extraction features or the detection of objects depends on the position of the cameras. In certain applications, the visibility of the target may vary; however, all visual systems require a camera layout to ensure acceptable image quality. Camera positioning depends on the location of cameras, obstacles available in sensitive areas and prioritized areas of the region. Therefore, the location issue becomes an optimization problem with relevant and competitive constraints. In this paper, a population-based optimization algorithm called Sine-Cosine Algorithm (SCA) is used to solve positioning problem. SCA creates several initial randomizations and requires using a mathematical model based on sinus and cosine functions, the outer side or the best way to move. Several random and suitable variables are also combined in this algorithm to explore and exploit the search space at the different milestones emphasizing the optimization.