SOURCE-LINKED INTELLIGENCE
A Multi-Modal AI Framework for Real-Time Queue Prediction, Management and Optimisation in Intelligent Border Control Systems
In the present work an efficient border control management procedure is proposed. Compared to operational queue management systems, whose operations are based on mostly static data, the proposed work takes into account dynamic traffic conditions, thus enabling optimal performance, even in cases of uncertainty. To this end, we are proposing a multi-modal Artificial Intelligence (AI) framework, tailored to th needs of border control systems, which enables real-time queue prediction, management, and resource optimization. The novel proposed approach integrates heterogeneous data sources and prese
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T11:55:40.000Z
First collected: 2026-09-21T08:51:59.673Z. This is not the publication date.