AI-BASED ADAPTIVE LEARNING in AR and VR ENVIRONMENT FOR ADVANCED CREW TRAINING TO ENHANCE MARITIME SAFETY

AR 和 VR 环境中基于人工智能的自适应学习，用于高级船员培训，以增强海上安全

• 批准号: 2872634
• 金额: --
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2872634
• 关键词: AI; BASED; ADAPTIVE; LEARNING; AR

In order to prevent an accident at sea, the maritime regulatory body, the International Maritime Organisation (IMO), has been adopting a set of rules and regulations. In addition to technical requirements, the International Maritime Organisation (IMO) established the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW). STCW Convention's aim is to establish basic requirements on training, certification, and watchkeeping for seafarers on an international level. However, due to the technology and demand ships have become more technologically advanced, complex, and autonomous requiring a more skilled workforce and hence the more advanced training. Similarly, development in Information technology, computing and artificial intelligence have also started transforming education. In recent years, more advanced AI-based learning systems are gaining recognition due to their ability to deliver learning objectives/contents and adapt to the individual needs of students. With Digitalisation, autonomy and communication systems, modern seafarers need not only to deal with the operation of the ships safely but also manage all the data effectively. AI-based adaptive training systems and competency assessments will be able to identify gaps in seafarers' knowledge and skills, and deliver personalised, targeted training programmes. However, while AI-Based adaptive learning methods are becoming popular for teaching, their implementation for the training of workers particularly seafarers has not been explored yet. The main aim of the PhD research is to enhance maritime safety through advanced training approaches by developing AI-based adaptive learning in AR and VR environments to deliver tailored training for individual crew. The specific objectives of the PhD research can be listed as- Identify the underlying human/organisational factors for maritime accidents by systematically analyzing the accident investigation reports- Develop solutions to mitigate these human/organisational underlying reasons for accidents- Review STCW training requirements and identify the gaps in the training contents and delivery. - Review the AI-based adaptive learning techniques and identify the most suitable and effective ones for training and VR environment. - Develop an AI application that can assess and measure a learner's previous subject knowledge, IT skills, and learning style based on the results from a number of answers to questions. - Based on the pre-assessment, develop a dynamic course creation tool that will build a course for each learner that is best suited to their profile whilst still consistently addressing all the required learning outcomes and meeting the standards required by the Maritime Awarding Bodies.- Integrate system into Full Mission Simulator and VR environment and test it systematically on groups of seafarers to quantify the effectiveness of the developed AI-based adaptive learning system.

为了防止海上发生事故，海事监管机构国际海事组织(IMO)一直在采用一套规则和条例。除技术要求外，国际海事组织(海事组织)还制定了《国际海员培训、发证和值班标准公约》(STCW)。STCW公约的目的是在国际层面上建立对海员的培训、认证和值班的基本要求。然而，由于技术和需求的原因，船舶在技术上变得更加先进、复杂和自主，需要更熟练的劳动力，因此需要更高级的培训。同样，信息技术、计算机和人工智能的发展也开始改变教育。近年来，更先进的基于人工智能的学习系统因其提供学习目标/内容和适应学生的个性化需求的能力而得到认可。随着数字化、自动化和通信系统的发展，现代海员不仅需要安全地处理船舶的运行，而且需要有效地管理所有的数据。基于人工智能的适应性培训系统和能力评估将能够找出海员知识和技能方面的差距，并提供个性化的、有针对性的培训方案。然而，尽管基于人工智能的自适应学习方法在教学中越来越受欢迎，但其在工人特别是海员培训中的实施还没有被探索。博士研究的主要目的是通过先进的培训方法，在AR和VR环境中开发基于人工智能的自适应学习，为个别船员提供量身定制的培训，从而提高海上安全。博士研究的具体目标可以列出如下：通过系统分析事故调查报告，找出导致海上事故的潜在人为/组织因素；制定解决方案，以减轻这些导致事故的人为/组织根本原因；审查STCW培训要求，并找出培训内容和交付方面的差距。-审查基于人工智能的自适应学习技术，并确定最适合培训和虚拟现实环境的最合适和有效的技术。-开发一款人工智能应用程序，该应用程序可以根据一系列问题的回答结果来评估和衡量学习者以前的学科知识、IT技能和学习风格。-在预先评估的基础上，开发一种动态课程创建工具，该工具将为每个学习者建立最适合他们的概况的课程，同时仍然始终如一地解决所有必要的学习结果，并达到海事授予机构要求的标准。-将系统集成到完整的任务模拟器和虚拟现实环境中，并在海员小组上进行系统测试，以量化开发的基于人工智能的自适应学习系统的有效性。