Surveillance camera systems are essential for construction monitoring tasks, including safety, productivity, progress tracking, and quality control. This paper investigates optimal design and dynamic adjustment of multi-camera systems across construction phases while minimizing cost. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model that incorporates evolving layouts, relocation costs, camera specifications, and risk-based priorities. As construction progresses, new obstacles can affect coverage, and the approach includes camera replacement across phases. The method was evaluated on a real-world case study involving four construction phases, achieving a 17.64 % cost reduction while maintaining effective coverage of high-priority zones. These results provide construction managers with a practical decision-support tool for adaptive and cost-efficient surveillance planning in dynamic environments. Nonetheless, the model is currently limited to two-dimensional layouts, and its practical application depends on the availability of sufficient computational resources for solving the exact optimization problem.

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