Advances in Urban Regional Development and Planning(AURDP)

Hitachi Rail, Toronto, Canada

Publications

• Research Article   
  AI-Driven Security Risk Mitigation: Enhancing Threat Assessment in Transit Infrastructure
  Author(s): Amirhossein Saali* and Raffaele Alfano
  
  The evolving threat landscape in transit infrastructure requires more adaptive, scalable, and precise security risk assessment and proposing proper risk mitigation measures. Traditional human-led approaches are often labor- intensive, subjective, and limited in their ability to incorporate real-time contextual data. This paper presents a novel AI-driven framework that combines geospatial analysis and large language models (LLMs) to automate the generation of structured, context-aware mitigation strategies aligned with industry standards and best practices. Our methodology involves a two-stage pipeline: (1) environmental feature extraction from Google Maps imagery and architectural design documentation, and (2) structured mitigation generation via controlled prompting of LLMs (GPT-3.5 and GPT-4.1) as two frequently used, and available models. We evaluate model performance across 320 re.. Read More»
  

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