Degree type
PhD
Closing date
1 June 2025
Campus
Launceston
Citizenship requirement
Domestic
About the research project
The maritime and shipping industry is being revolutionised by digitalisation and implementation of Industry 4.0. The IoT, AI, and virtualisation technologies have allowed the development of autonomous and unmanned approaches for the operation of surface vehicles. Literature shows these changes can significantly improve maritime operations' safety and efficiency [1, 2]. In addition, the operational flexibility of the new approach can lead to reduced onboard crew requirements. These improvements perfectly align with the shipping industry's focus on decarbonisation [3].
These changes also come with their own set of challenges that directly affect human labour [4]. Despite the term "unmanned" often used to describe the new maritime operation, there will continue to be marine engineers and technicians on board these ships for the foreseeable future [5]. However, next generation of seafarers and remote operators must possess a unique blend of traditional maritime knowledge and expertise in new technologies. Familiarity with automation systems, communication infrastructure, and their inherent quirks will be crucial [6]. Additionally, adaptability and problem-solving skills will be paramount for navigating complex, high-pressure environments, particularly when encountering unexpected situations or system malfunctions [7]. Traditional training methods, primarily focused on hands-on experience aboard vessels, are becoming less efficient in preparing future maritime personnel for the complexities of operating increasingly sophisticated vessels due to their lack of realism and feedback. Furthermore, the current solution of bridge simulators suffers from a lack of standardisation and often employs subjective assessment techniques. Existing simulators are primarily designed for training routine operations and may not adequately address critical incident scenarios [8]. These limitations necessitate the exploration of alternative training solutions [9].
This project aims to tackle these challenges with an advanced simulation module, which can be used as a surface vehicle virtual representation or digital twin system and a valuable tool for training future maritime workforce. The simulation will focus on developing essential skills and situational responses for seafarers and remote operators. For instance, the simulation training modules for remote vessel operation may include navigation, ship manoeuvring in dynamic weather and traffic conditions, and emergency response procedures. To assist the learning experience, mixed reality technology may be integrated to provide flexibility to the trainee's familiarising process of working on board [10]. Mixed reality simulating technology may also be utilised to create a digital representation of unmanned surface vehicles, allowing for bidirectional communication and control between the physical ship and remote operator. Machine intelligence can also be helpful in the learning process by generating personalised feedback and guidance for trainees [11]. Given the novelty of the knowledge domain in the advanced simulation and digital twin as a training tool in unmanned shipping, a comprehensive evaluation to assess the effectiveness of the developed solution needs to be carried out with measuring factors such as trainees' knowledge interpretation and knowledge retention [12].
This project can be divided into three phases: Research, Design, and Evaluation. A comprehensive review of maritime training, simulation training technologies, and skill development will be conducted in the initial phase. Besides the literature review, opinions from maritime stakeholders such as shipping companies' personnel, maritime educators, and autonomous shipping technology providers can also provide valuable insights for developing the simulation system. In the second phase, the design of advanced simulation modules and the development of the tool will be carried out. Lastly, the evaluation process will be performed iteratively, with multiple rounds conducted at different locations and with varying data sizes and numbers of participants. This iterative approach allows testing the system under diverse scenarios and enables the developer to fine-tune the system based on collected pre and post-training assessments, observations, and trainees' feedback.
The anticipated outcome of this research project is an advanced simulation module that can be seamlessly integrated into the existing maritime infrastructure and training programs for future seafarers and remote vessel operators. To complement the simulator, the project will also create implementation guidelines. These guidelines will assist institutions in effectively transitioning to the new training programs and employing the advanced simulation and digital twin tool for USV monitoring and control operation.
References
[1] Shahbakhsh, M., Emad, G., & Cahoon, S. (2021). Industrial revolutions and transition of the maritime industry: The case of Seafarer's role in autonomous shipping, Asian Journal of Shipping and Logistics
[2] Emad, G. (2010). Introduction of Technology into Workplace and the Need for Change in Pedagogy, Procedia - Social and Behavioral Sciences 2(2), 875–879.
[3] Nazir, S., Øvergård, K. I., & Yang , Z. (2015). Towards Effective Training for Process and Maritime Industries. Procedia Manufacturing, 3, 1519-1526.
[4] Emad, G. R. (2020). Shipping 4.0 disruption and its impending impact on maritime education. In Disrupting Business as Usual in Engineering Education (pp. 202-207). Barton, ACT: Engineers Australia.
[5] Shahbakhsh, M., Emad, G., & Cahoon, S. (2021). Industrial revolutions and transition of the maritime industry: The case of Seafarer's role in autonomous shipping, Asian Journal of Shipping and Logistics
[6] Emad, G. R., Enshaei, H, & Ghosh, S (2021). Seafarer Training Needs for Operating Future Autonomous Ships: A systematic review, Australian Journal of Maritime & Ocean Affairs. https://doi.org/10.1080/18366503.2021.1941725
[7] Emad, G. R. & Ghosh, S, (2023). Identifying Essential Skills and Competencies Towards Building a Training Framework for Future Operators of Autonomous Ships: A qualitative study, WMU Journal of Maritime Affairs, pp. 1-19. doi:10.1007/s13437-023-00310-9
[8] Masodzadeh, P. G., Ölçer, A. I., Ballini, F., & Christodoulou, A. (2022). A review on barriers to and solutions for shipping decarbonization: What could be the best policy approach for shipping decarbonization? Marine Pollution Bulletin, 184.
[9] Emad, G. (2010). Introduction of Technology into Workplace and the Need for Change in Pedagogy, Procedia - Social and Behavioral Sciences 2(2), 875–879.
[10] Ke, F., Lee, S., & Xu, X. (2016). Teaching training in a mixed-reality integrated learning environment. Computers in Human Behavior, 62, 212-220.
[11] LEE, A. V. (2023). Supporting students' generation of feedback in large-scale online course with artificial intelligence-enabled evaluation. Studies in Educational Evaluation, 77.
[12] Ghosh, S. and Emad G. (2024). Developing and Implementing a Skills and Competency Framework for MASS Operators: Opportunities and Challenges, In Proceedings of the International Conference on Maritime Autonomy and Remote Navigation (ICMAR NAV) Nov 2023, Launceston, Australia, pp. 1-7.
Primary Supervisor
Funding
Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:
- a living allowance stipend of $33,511 per annum (2025 rate, indexed annually) for 3.5 years
- a relocation allowance of up to $2,000
- a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)
If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.
As part of the application process you may indicate if you do not wish to be considered for scholarship funding.
Other funding opportunities and fees
For further information regarding other scholarships on offer, and the various fees of undertaking a research degree, please visit Scholarships and fees.
Eligibility
Applicants should review the Higher Degree by Research minimum entry requirements.
Ensure your eligibility for the scholarship round by referring to our Key Dates.
Additional eligibility criteria specific to this project/scholarship:
- Applicants must be able to undertake the project on-campus
Selection Criteria
The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.
Additional desirable selection criteria specific to this project:
- The experience in the maritime domain is desirable for this project. The familiarity with simulation and virtualisation technology, especially with programming and coding ability is preferred.
Application process
- Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
- Contact Dr Reza Emad to discuss your suitability and the project's requirements; and
- In your application:
- Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
- Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
- Apply prior to 1 June 2025.
Full details of the application process can be found under the 'How to apply' section at Research degrees.
Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.
Apply now Explore other projects
Why the University of Tasmania?
Worldwide reputation for research excellence
Quality supervision and support
