Using Evolutionary Approaches to Manage Surveillance Cameras in Dynamic Environments

摘要

The efficient management (placement and orientation) of surveillance cameras within a floor plan is a well-known and difficult problem that has regained attention. The objective is to locate the minimum number of cameras in a physical space to ensure important walls are within the view of at least one camera. Heuristic-based approaches have been developed for this NP-hard problem; unfortunately, most do not consider the dynamic conditions that may occur in reality. In these situations, camera availability may change, coverage requirements may be updated, and/or camera movement may be limited. This paper investigates evolutionary-based techniques to manage surveillance cameras under dynamic conditions. Using an evolutionary-based approach, a surveillance configuration (camera locations and orientations) is encoded as a chromosome and evolutionary processes are applied to identify better solutions over successive generations. The approach has the ability to identify efficient surveillance configurations (minimum number of cameras with maximum coverage); however, another advantage is the ability to adapt if the environment changes. Simulation results demonstrate that evolutionary-based approaches can successfully manage surveillance cameras under dynamic conditions.