Camera placement optimization for CCTV in rail transit using BIM

Abstract

In an environment where completely automated lines are gaining popularity, station service employees are declining yearly while passenger volume increases. In many cities, the need for station video surveillance with “complete coverage without dead ends” has been high. The traditional layout scheme based on design experience estimates often results in large blind spots and low efficiency in monitoring. In order to solve this problem, based on BIM technology, this work develops a quantified camera layout optimization approach employing an improved genetic algorithm. The plan includes three modules: the data extraction, which extracts the spatial information of the functional area from the BIM model to generate a data image; the optimization module, which adopts the improved genetic algorithm and uses the pixel coordinates provided by the data image to realize the camera pre-deployment; the visualization module, which designs the simulation plug-in through BIM secondary development technology, simulates and verifies the pre-deployment, and provides the solutions. The approach’s effectiveness was confirmed by verifying the deployment optimization at the station platform level. The optimal solution’s camera coverage is 27.2% better than the experience-based camera layout.