AI-Enabled Surveillance Systems in the Context of National Security and Critical Infrastructure Protection
AI-Enabled Surveillance Systems in the Context of National Security and Critical Infrastructure Protection

Summary/Abstract: The article examines whether and to what extent AI-based motion and behavior pattern recognition can enhance both safety and security at train stations. To answer this research question, secondary research was conducted through a comprehensive literature review. The findings indicate that AI-supported video surveillance is essential for effective safety and security management, as it overcomes the human limitations of conventional monitoring systems. These technologies can identify and track individuals and objects, interpret behavior, and distinguish between relevant and irrelevant activities – although their performance is heavily dependent on the quality of the training data used. The systems learn typical behavior patterns and can automatically trig-ger alerts in case of deviations. This enables the detection of crowd dynamics, group behavior, and potentially dangerous situations, as well as the timely response to security-related incidents such as pickpocketing, unauthorized access to tracks, acts of vandalism, or even terrorism and sabotage. As a result, security personnel can be used more eficiently, and the public’s sense of safety and security can be strengthened. Despite concerns regarding data protection, initial legal frameworks demonstrate that clear regulatory conditions can be established to legitimize the use of such technologies.

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