Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships
https://orcid.org/0000-0002-3795-7856
https://orcid.org/0000-0003-4040-4491
Piracy and armed robbery continue to pose significant security threats to the shipping industry. This paper presents a real-time threat assessment and crisis classification tool for piracy or armed robbery incidents. The tool is part of a crisis classification module that addresses various categories of security threats. This module is currently being developed as part of the EU-funded research project ISOLA, which aims to introduce an intelligent security superintendence ecosystem. The ecosystem is designed to complement the existing ship security processes and measures applied onboard passenger ships. The tool operates by providing real-time threat classification and subsequent warnings by analysing data collected from the ship’s legacy systems and installed sensors with the utilisation of Bayesian probabilistic techniques, particularly Bayesian Networks. The BN model developed for this purpose is thoroughly examined, and its validation is presented through indicative case studies involving piracy and armed robbery. The main objective is to improve situational awareness, enhance vigilance and early threat detection, and support the decision-making process for the Master and crew, especially under time-sensitive circumstances and stressful conditions.
A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships
https://orcid.org/0000-0002-3795-7856
https://orcid.org/0000-0003-4040-4491
Piracy and armed robbery continue to pose significant security threats to the shipping industry. This paper presents a real-time threat assessment and crisis classification tool for piracy or armed robbery incidents. The tool is part of a crisis classification module that addresses various categories of security threats. This module is currently being developed as part of the EU-funded research project ISOLA, which aims to introduce an intelligent security superintendence ecosystem. The ecosystem is designed to complement the existing ship security processes and measures applied onboard passenger ships. The tool operates by providing real-time threat classification and subsequent warnings by analysing data collected from the ship’s legacy systems and installed sensors with the utilisation of Bayesian probabilistic techniques, particularly Bayesian Networks. The BN model developed for this purpose is thoroughly examined, and its validation is presented through indicative case studies involving piracy and armed robbery. The main objective is to improve situational awareness, enhance vigilance and early threat detection, and support the decision-making process for the Master and crew, especially under time-sensitive circumstances and stressful conditions.
A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships
https://orcid.org/0000-0002-3795-7856
https://orcid.org/0000-0003-4040-4491
Piracy and armed robbery continue to pose significant security threats to the shipping industry. This paper presents a real-time threat assessment and crisis classification tool for piracy or armed robbery incidents. The tool is part of a crisis classification module that addresses various categories of security threats. This module is currently being developed as part of the EU-funded research project ISOLA, which aims to introduce an intelligent security superintendence ecosystem. The ecosystem is designed to complement the existing ship security processes and measures applied onboard passenger ships. The tool operates by providing real-time threat classification and subsequent warnings by analysing data collected from the ship’s legacy systems and installed sensors with the utilisation of Bayesian probabilistic techniques, particularly Bayesian Networks. The BN model developed for this purpose is thoroughly examined, and its validation is presented through indicative case studies involving piracy and armed robbery. The main objective is to improve situational awareness, enhance vigilance and early threat detection, and support the decision-making process for the Master and crew, especially under time-sensitive circumstances and stressful conditions.
A Bayesian network-based tool for crisis classification in piracy or armed robbery incidents on passenger ships
Ventikos, Nikolaos P. (Autor:in) / Koimtzoglou, Alexandros (Autor:in) / Michelis, Alexandros (Autor:in) / Stouraiti, Angeliki (Autor:in) / Kopsacheilis, Ioannis (Autor:in) / Podimatas, Vassilis (Autor:in)
01.05.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
MPA Hosts IMO Seminar on Piracy, Armed Robbery
British Library Online Contents | 1999
MPA:IMO officials promoting inter-government efforts to fight piracy and armed robbery
British Library Online Contents | 2001
Discussion on Technical Defense against Piracy for Ocean-Going Ships
| British Library Conference Proceedings | 2011
British Library Online Contents | 1999
Diagnosing Distresses of Embankment Dams using Bayesian Network Based on 150 Incidents
| British Library Conference Proceedings | 2009