Surveillance system is becoming an indispensable system on construction sites with the fast development of computer vision techniques, thus an optimal placement of surveillance cameras is essential for the successful performance of this system. However, to develop effective models and solutions for large-scale camera placement still remain as opening challenges. Therefore, this study investigated two fundamental placement problems and proposed a multiobjective placement problem, where the maximum-coverage problem is to monitor the construction layout as much as possible with a limited budget; the minimum-cost problem is to minimize the cost given a layout required to be fully covered; and the multiobjective problem is to identify the Pareto fronts of cost and coverage ratio of the system. To solve these problems, the objective space and search space were discretized, and the deterministic and heuristic approaches were revised and developed to provide effective solutions. Finally, experiments in a practical project in Hong Kong were conducted to verify the sufficiency of the developed algorithms and findings revealed potential implementations in many scenarios.
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