Leveraging Digital Twin Technologies for Public Space Protection and Vulnerability Assessment
Artemis Stefanidou, Jorgen Cani, Thomas Papadopoulos, Panagiotis, Radoglou-Grammatikis, Panagiotis Sarigiannidis, Iraklis Varlamis, Georgios, Th. Papadopoulos

TL;DR
This paper introduces a Digital Twin-based security framework that integrates IoT, AI, and big data to enhance real-time protection and vulnerability assessment of public spaces against complex threats.
Contribution
It presents a novel Digital Twin-as-a-Security-Service architecture combining multiple advanced technologies for holistic, real-time security management of public spaces.
Findings
Effective threat detection in large public areas
Enhanced vulnerability assessment capabilities
Robustness demonstrated in real-world scenarios
Abstract
Over the recent years, the protection of the so-called `soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has emerged as a rather challenging and increasingly important issue. The complexity and seriousness of this security threat growths nowadays exponentially, due to the emergence of new advanced technologies (e.g. Artificial Intelligence (AI), Autonomous Vehicles (AVs), 3D printing, etc.); especially when it comes to large-scale, popular and diverse public spaces. In this paper, a novel Digital Twin-as-a-Security-Service (DTaaSS) architecture is introduced for holistically and significantly enhancing the protection of public spaces (e.g. metro stations, leisure sites, urban squares, etc.). The proposed framework combines a Digital Twin (DT) conceptualization with additional cutting-edge technologies, including…
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Taxonomy
TopicsDigital Transformation in Industry
