Abstract
Counter-terrorism and its preventive and response actions are crucial factors in security planning and protection of mass events, soft targets and critical infrastructures in urban environments. This paper presents a comprehensive Decision Support System developed under the umbrella of the S4AllCitites project, that can be integrated with legacy systems deployed in the Smart Cities. The system includes urban pedestrian and vehicular evacuation, considering ad-hoc predictive models of the evolution of incendiary and mass shooting attacks in conjunction with a probabilistic model for threat assessment in case of improvised explosive devices. The main objective of the system is to provide decision support to public or private security operators in the planning and real time phases in the prevention or intervention against a possible attack, providing information on evacuation strategies, the probability or expected impact of terrorist threats and the state of the traffic network in normal or unusual conditions allowing the emergency to be managed throughout its evolution.
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References
Abreu, O., Cuesta, A., Balboa, A., Alvear, D.: On the use of stochastic simulations to explore the impact of human parameters on mass public shooting attacks. Saf. Sci. 120, 941–949 (2019)
Anees, V., Kumar, G.: Direction estimation of crowd flow in surveillance videos. In: 2017 IEEE Region 10 Symposium (TENSYMP), pp. 1–5 (2017)
Araujo, A., Cacho, N., Thome, A., Medeiros, A., Borges, J.: A predictive policing application to support patrol planning in smart cities. In: 2017 International Smart Cities Conference (ISC2), pp. 1–6 (2017)
Balla, P.B., Jadhao, K.: IoT based facial recognition security system. In: 2018 International Conference on Smart City and Emerging Technology (ICSCET), pp. 1–4 (2018)
Bellini, P., Cenni, D., Nesi, P., Paoli, I.: Wi-Fi based city users’ behaviour analysis for smart city. J. Vis. Lang. Comput. 42, 31–45 (2017)
Bonatsos, A., Middleton, L., Melas, P., Sabeur, Z.: Crime open data aggregation and management for the design of safer spaces in urban environments. In: International Symposium on Environmental Software Systems, pp. 311–320 (2013)
Boukerche, A., Siddiqui, A., Mammeri, A.: Automated vehicle detection and classification: models, methods, and techniques. ACM Comput. Surv. (CSUR) 50(5), 1–39 (2017)
Brust, M.R., Danoy, G., Bouvry, P., Gashi, D., Pathak, H., Gonçalves, M.P.: Defending against intrusion of malicious UAVs with networked Uav defense swarms. In: 2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops), pp. 103–111 (2017)
Chackravarthy, S., Schmitt, S., Yang, L.: Intelligent crime anomaly detection in smart cities using deep learning. In: 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC), p. 399–404 (2018)
Cuesta, A., Abreu, O., Balboa, A., Alvear, D.: A new approach to protect soft-targets from terrorist attacks. Saf. Sci. 120, 877–885 (2019)
Dbouk, M., Mcheick, H., Sbeity, I.: CityPro; an integrated city-protection collaborative platform. Procedia Comput. Sci. 37, 72–79 (2014)
Dial, R.B.: A path-based user-equilibrium traffic assignment algorithm that obviates path storage and enumeration. Transp. Res. Part B Methodol. 40(10), 917–936 (2006)
EUROPOL: European union terrorism situation and trend report (2021)
Fernández, J., et al.: An intelligent surveillance platform for large metropolitan areas with dense sensor deployment. Sensors 13(6), 7414–7442 (2013)
Global Terrorism Database™ (GTD): Obtenido de (2021). https://www.start.umd.edu/gtd/
Hartama, D., et al.: A research framework of disaster traffic management to Smart City. In: 2017 Second International Conference on Informatics and Computing (ICIC), pp. 1–5 (2017)
Helbing, D., Molnár, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51(5), 4282 (1995)
Jayakrishnan, R., Tsai, W.T., Prashker, J.N., Rajadhyaksha, S.: A faster path-based algorithm for traffic assignment (1994)
Jedlicka, K., et al.: Traffic modelling for the smart city of Pilsen (2020)
Kolovský, F., Ježek, J., Kolingerová, I.: The origin-destination matrix estimation for large transportation models in an uncongested network. In: International Conference on Mathematical Applications, pp. 17–22 (2018)
Laufs, J., Borrion, H., Bradford, B.: Security and the smart city: a systematic review. Sustain. Cities Soc. 55, 102023 (2020)
Martin, R.H.: Soft targets are easy terror targets: increased frequency of attacks, practical preparation, and prevention. Forensic Res. Criminol. Int. J. 3(2), 1–7 (2016)
McGrattan, K., et al.: Fire Dynamics Simulator User’s Guide. National Institute of Standards and Technology (2017)
Noor, M., Nawawi, W., Ghazali, A.: Supporting decision making in situational crime prevention using fuzzy association rule. In: 2013 International Conference on Computer, Control, Informatics and Its Applications (IC3INA), pp. 225–229 (2013)
Spiess, H.: A gradient approach for the OD matrix adjustment problem. \({\text{a}} \in {\hat{\text{A}}}\), 1 (1990)
Truntsevsky, Y.V., Lukiny, I., Sumachev, A., Kopytova, A.: A smart city is a safe city: the current status of street crime and its victim prevention using a digital application. In: MATEC Web of Conferences, vol. 170, p. 01067 (2018)
Tuman, J.S.: Communicating Terror: The Rhetorical Dimensions of Terrorism. Sage Publications (2009)
Turban, E.: Decision Support and Expert Systems Management Support Systems. Prentice-Hall, Inc., Hoboken (1995)
Zhang, W., et al.: Agent-based modeling of a stadium evacuation in a smart city. In: 2018 Winter Simulation Conference (WSC), pp. 2803–2814 (2018)
Zhou, W., Saha, D., Rangarajan, S.: A system architecture to aggregate video surveillance data in Smart Cities. In: 2015 IEEE Global Communications Conference (GLOBECOM), pp. 1–7 (2015)
Zingoni, A., Diani, M., Corsini, G.: A flexible algorithm for detecting challenging moving objects in real-time within IR video sequences. Remote Sens. 9(11), 1128 (2017)
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The project (S4AllCities) has received funding from the European Union’s H2020 research and innovation programme under grant agreement No. 883522.
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González-Villa, J. et al. (2022). Decision-Support System for Safety and Security Assessment and Management in Smart Cities. In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022. Lecture Notes in Computer Science, vol 13374. Springer, Cham. https://doi.org/10.1007/978-3-031-13324-4_3
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