AI-Based Assistance System for Control Rooms in Large-Scale Infrastructures

Abstract

An AI-based approach to supporting control rooms in large-scale infrastructures is presented. Distributed data sources, unclear documentation, and complex system depen-dencies make rapid and reliable decision-making difficult in such environments. The developed assistance system consolidates knowledge from operating manuals, experiential expertise, and real-time data, and makes it accessible through a natural language interface. Technically, the system is based on a locally operated multi-agent architecture that integrates data from moni-toring and control software. A verifiable workflow with fixed feedback loops ensures that inputs and outputs remain traceable and stable. This makes it possible to translate probabilistic mod-els into comprehensible and reproducible action steps—an essential aspect for deployment in safety-critical environments. The development and testing take place in scientific facilities being established at DESY Zeuthen. The paper describes initial results, challenges related to data quality and integration, and the potential contributions of the approach to resilient, transparent, and sustainable AI support systems for control rooms.