BIM-based framework for optimization of CCTV surveillance in buildings

Surveillance cameras are becoming an integral part of the buildings due to their ability to ensure security, as well as to promote safety and overall well-being. Finding the optimal camera configuration remains a challenge, as current practices depend heavily on professional experience and subjective judgment. These practices have several limitations which can adversely impact camera coverage. Building information modelling (BIM) usage is growing in the industry due to its ability to generate accurate spatial data. Therefore, this study proposes a BIM-based framework to optimize camera placement process using optimization algorithms (OAs). Firstly, the framework extracts spatial data of the target area from the BIM based on user defined requirements. Secondly, it adopts an optimization algorithm to find the optimal camera positions for the target area based on the user requirement. The selection of optimization algorithm was made following a comparative evaluation between Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Lastly, it helps visualize the optimized results within the building using BIM. The framework was validated on a hospital building, revealing 27% increase in coverage, a significant reduction in overlap, and a lower camera requirement compared to experience-based camera configuration.