The impact of voluntary artificial intelligent self-driven education and training platforms on maritime security personnel: ISPS code

Ahmed Mohy Ibrahim ()
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Ahmed Mohy Ibrahim: Regional Maritime Security Institute (RMSI), Arab Academy for Science, Technology and Maritime Transport, (AASTMT)

Journal of Transportation Security, 2024, vol. 17, issue 1, No 20, 18 pages

Abstract: Abstract The maritime security threats, including cyber threats, have highlighted the need for innovative solutions in the industry. Artificial intelligence (AI) offers significant potential to address these challenges by improving decision-making, and enhancing threat detection, by strengthening Maritime Security Personnel’s (MSPs) capabilities. Utilizing a descriptive-analytical methodology, this study explores the potential of integrating AI-driven platforms and voluntary self-development initiatives to elevate MSP’s capabilities. This paper aims to explore how the multifaceted challenges and opportunities integration of AI, alongside human expertise, offers significant transformative solutions to the dynamic challenges of maritime security, including enhanced skills, heightened security awareness, and personal capacity building, all aimed at bridging the knowledge and skills gaps essential for proactive security measures. While recognizing the existing challenges, such as technology resistance, time constraints, and financial limitations, are acknowledged in this study, it goes a step further by demonstrating successful integration strategies that embrace new technologies. Equipping MSPs with tailored maritime security learning experiences, with the fusion of artificial intelligent self-driven education and training (AI-SDET) platforms, would have the potential to significantly contribute to boosting reliability and resilience within the smart maritime industry development.

Keywords: Maritime security; ISPS code; Artificial intelligence foundation; Self-capacity building; MET (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12198-024-00292-6

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