González-Villa, J., Cuesta, A., Spagnolo, M., Zanotti, M., Summers, L., Elms, A., Dhaya, A., Jedlička, K., Martolos, J. and Cetinkaya, D., 2023. Decision-support system for safety and security assessment and management in smart cities. Multimedia Tools and Applications, 83, 61971-61994.
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DOI: 10.1007/s11042-023-16020-6
Abstract
Counter-terrorism measures and preparedness play a critical role in securing mass gatherings, soft targets, and critical infrastructures within urban environments. This paper introduces a comprehensive Decision Support System developed as part of the S4AllCitites project, designed to seamlessly integrate with existing legacy systems in Smart Cities. The system encompasses urban pedestrian and vehicular evacuation, incorporating predictive models to anticipate the progression of incendiary and mass shooting attacks, alongside a probabilistic model for threat assessment in the case of improvised explosive devices. A notable achievement of this research is the successful implementation and deployment of the system in operational environments through pilot studies. It empowers public and private security operators with real time decision support capabilities during both prevention and intervention stages of potential attacks. The decision support information provided encompasses various aspects, including optimal evacuation strategies, estimated egress times, pedestrian movement profiles, probability assessments, and the potential impact of different terrorist threats in terms of casualties. Additionally, the system offers real-time insights into the status of the traffic network under normal and unusual conditions, enabling efficient emergency management throughout its progression. This includes the ability to identify optimal intervention routes and assess the impact of anomalous traffic resulting from evacuations.
Item Type: | Article |
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ISSN: | 1380-7501 |
Uncontrolled Keywords: | Decision Support System; Evacuation; Fire and Smoke; Security and Safety; Simulation; Terrorism; Threats; Traffic |
Group: | Faculty of Science & Technology |
ID Code: | 38778 |
Deposited By: | Symplectic RT2 |
Deposited On: | 13 Jul 2023 13:14 |
Last Modified: | 03 Jul 2024 08:22 |
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