Optimal Placement Method for Substation Surveillance Cameras Based on Dynamic Programming

The optimization of the position and orientation of surveillance cameras is commonly regarded as a discrete combinatorial optimization problem. Traditional placement methods aim to maximize the monitoring coverage of camera arrays or minimize the cost of installing cameras while employing approximation techniques to derive the approximate optimal solution for the placement optimization problem. However, these methods are premised on the assumption of equally significant grid cells, which overlooks the actual monitoring demands of the target area. In this paper, we initiate a risk assessment of the monitoring area of the substation and assess the importance of grid points in the area to identify security-sensitive areas. We then employ a dynamic programming approach to resolve the risk-quantified area and obtain the optimal placement scheme for surveillance cameras. The case study findings demonstrate that the proposed method can considerably enhance the monitoring efficiency of surveillance cameras in substations and achieve effective monitoring of key areas.