Situation-Aware Adaptive Interfaces for Cultural Heritage based on Oscillatory Attention Dynamics

The monitoring and preservation of cultural heritage (CH) sites often rely on human operators supported by digital interfaces. However, goal-driven attention and information overload may impair the operator's ability to respond effectively to critical events. This paper introduces a novel approach to developing situation-Aware adaptive interfaces, grounded in neuroscientific models of human attention. Specifically, we propose a mathematical model based on oscillatory dynamics and a simplified Markovian process to simulate transitions between cognitive states-from routine monitoring to critical alert. These transitions are influenced by environmental data, such as rainfall intensity and rate of change. A case study based on the archaeological site of Pompeii demonstrates how the proposed interface can adapt its behavior in real time, enhancing operator awareness and responsiveness, while minimizing distraction. This mechanism supports predictive maintenance and provides a more natural and effective human-machine interaction paradigm.