About Course
As the maritime industry advances toward smarter and more connected vessels, the ability to monitor, maintain, and optimise ship systems through digital technologies has become essential for improving operational reliability, safety, and efficiency.
In this course, learners are introduced to the foundations of smart ship operations, beginning with an overview of remote monitoring in maritime environments and the evolving ecosystem of sensors, data acquisition systems, and communication networks that enable connected shipboard infrastructure.
Building on this foundation, the programme explores how remote monitoring and inspection technologies are applied in practice, including the use of Internet of Things (IoT) devices, Augmented and Virtual Reality (AR/VR) platforms, and Non-Destructive Testing (NDT) techniques to support remote collaboration, inspection, and maintenance activities.
The course also examines how operational data can be processed, analysed, and visualised to support predictive maintenance and data-driven decision-making. Participants will gain exposure to modelling, simulation, and Artificial Intelligence (AI) techniques that enhance anomaly detection and system reliability, while also learning how classification society notations and guidelines shape the implementation of remote surveys and smart ship technologies.
Who Should Attend
This course is suitable for:
Minimum Entry Requirements
- Participants should have at least a Polytechnic Diploma or equivalent work experience in the marine, offshore, or related engineering/technical sectors.
- Basic technical literacy and familiarity with IT or engineering concepts.
Learning Outcomes
By the end of this course, participants will be able to:
- Explain the architecture and evolution of remote monitoring and inspection technologies in the maritime and offshore sectors.
- Identify and integrate key components of shipboard monitoring systems including IoT sensors, data acquisition units, and communication networks.
- Apply NDT and drone-based inspection methods to evaluate hull and machinery integrity.
- Analyse and visualise operational data using analytics and predictive tools to support data-driven maintenance decisions.
- Interpret and apply classification society notations and guidelines related to remote surveys and smart ship certifications.
- Leverage modeling, simulation, and AI techniques for predictive maintenance and anomaly detection.
- Utilise AR/VR and mixed reality platforms for remote collaboration, training, and inspection support.
- Develop and present a conceptual remote monitoring and inspection strategy that enhances ship safety, compliance, and operational efficiency.
Teaching Team
Ang Joo Hock
Associate Professor, Singapore Institute of Technology (SIT)
Bernard Voon Ee How
Associate Professor, Principal Investigator, Offshore & Marine Digital Learning Lab (in collaboration with Seatrium)
Zhou Junhong
Associate Professor, Engineering, Singapore Institute of Technology
Course Details
Learning Hours
Total: 16 hours
- Classroom Facilitated Training: 13.5 hours
- Assessment: 2.5 hours
Certificate and Assessment
Certificate of Participation and Certificate of Attainment
Assessment Plan
Mode of Assessment: Project and Written Exam
Fee Structure
The full fee for this course is S$2,616.00.
| Funding Category | Eligible Funding | Course Fees Payable After Funding |
|---|---|---|
| Singapore Citizen (Below 40) | 70% | S$784.80 |
| Singapore Citizen (Above 40) Funded under SkillsFuture Mid-Career Enhanced Subsidy (MCES) | 90% | S$304.80 |
| Singapore PR / LTVP+ Holder | 70% | S$784.80 |
| Non-Singapore Citizen | Not Eligible | S$2,616 |
Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.
Course Runs
Learning Pathway
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