An IoT/IoE-Based Integrated Security and Safety System for the Royal Palace and Gardens of Caserta, with a Genetic-Algorithm Method for the Optimal Design of Perimeter Video Surveillance

Monumental heritage sites must be protected as rigorously as critical infrastructures, but under aesthetic and architectural constraints that limit where protection technologies can be installed; the purpose of this study is to reconcile effective security with minimal impact on the historical fabric. The paper presents the integrated security and safety system realized for the Royal Palace and Gardens of Caserta, a UNESCO World Heritage Site visited by around one million people per year. This system includes an Internet of Things/Internet of Everything framework integrating a 3D supervision platform, a resilient park-wide network, video surveillance, emergency communications, an artificial-intelligence engine and visitor services. Perimeter video-surveillance design is formulated as a constrained multi-objective optimization problem (coverage, camera count, overlap, reuse of existing installation points) solved with a purpose-built genetic algorithm and characterized through 311 optimization runs and 216 baseline runs on synthetic perimeter instances. The algorithm reached 95–98% perimeter coverage while reusing 95–100% of existing installation points, converging within 120–410 generations. Two greedy baselines were respectively quantified: the price of the aesthetic objectives (a 29–41% camera overhead with respect to a coverage-only design) and the specific contribution of the joint optimization (an order-of-magnitude reduction in coverage redundancy at equal reuse of existing installation points). Sensitivity analysis exposed the coverage–cost trade-off. The framework and method provide a reproducible, quantitatively characterized approach to minimally invasive heritage security design that is transferable to comparable sites.