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Brainstorming about the Impact of Artificial Intelligence (AI) Applications upon the Shipping Industry

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Abstract

“Artificial Intelligence” (AI) can be defined as the simulation of human intelligence processes by “machines”, especially computer systems. It is a rather common knowledge that AI has already helped numerous organizations to boost their revenues by streamlining the related business procedures, automating repetitive jobs, and improving customer service. Therefore, it is not a coincidence that the financial impact of AI applications and pompous terms like “How generative AI will reshape the enterprise?” have recently dominated the public sphere. It is a rather self-explanatory fact that AI has the potential to lead to a massive productivity boom –but one which won’t be shared equally across economies around the world. When the discussion is shifted to the wider shipping industry, the so-called “Digitalization” phenomenon, which also includes the topic of “Maritime Autonomous Surface Ships (MASS), provides a quite disruptive picture of how this industry may be transformed in the near future. The rather simplistic and most times confusing term "Autonomous Vessels" is often used to describe systems that -to some extend- are able to make decisions by themselves, requiring no human input. Indicative examples of AI applications of immediate interest for shipping include expert systems, natural language processing, speech recognition and machine vision (among others). Furthermore, it is necessary to consider that the hardware element of sensors on board contemporary ships has already kind of “exhausted” the room of further improvement; the use of advanced software applications and utilisation of AI tools to improve more the capabilities of the various systems used to support the conduct of navigation seems can be viewed as the best alternative way forward. This briefing will firstly provide the necessary definitions/clarifications in relation to MASS and AI applications. Then, it will explain the reasons why only advanced AI tools can pave the way towards autonomous systems and eventually to fully unmanned (or, uncrewed) ships. Finally, it will briefly explore what tools are available today to help “humans” and “machines” effectively collaborate together in the same working environment (i.e., image and/or speech recognition). A conclusion standing out is that building, improving and running AI applications requires immense computing power; a Cloud-based architecture can offer that in a flexible and easy “scalable” environment (at relatively low-cost and without huge initial investments). In addition, effective management of “Big Data” and deploying the right analytical tools should be approached as a prerequisite for AI and in turn, AI applications can provide the solution to process unstructured data and derive useful insights from it.
Dr. Dimitrios Dalaklis, Professor (Safety and Security)
Brainstorming about the Impact of Artificial Intelligence (AI)
Applications upon the Shipping Industry
Introduction (including familiarization with WMU);
Discussing the framework of Definitions;
Maritime Autonomous Surface Ships (MASS) and
the role of AI in future operations;
Questions & Answers
Outline
Maritime Post-Graduate University;
Focus on Maritime Education, Capacity-
Building & Research.
Established by the International
Maritime Organisation (IMO) in 1983;
(IMO is the United Nations specialized
agency with responsibility for the safety
and security of shipping and the
prevention of marine and atmospheric
pollution by ships…)
World Maritime University (WMU), in Malmö-Sweden.
Issues to Consider during Introduction:
Shipping In the Era of Digitalisation/possible changes?
Disruptive trends of Internet of Things (IoT), Artificial
Intelligence (AI) and Big Data (among others ) that look
set to change established practices;
Drivers like efficiency, regulation and to keep up with
competition”…
Industry 4.0: A New Operating Paradigm?
Favourite Academic Topic: Definitions!
Human Brain vs Artificial Intelligence (AI):
https://www2.deloitte.com/se/sv/pages/technology/articles/part1-artificial-intelligence-defined.html
Points to note:
MOVING FAST! During the previous stages of
industrial revolution, it has often taken decades to
build the training systems and labour market
institutions needed to develop new skillsets on a
large scale.
Artificial intelligence is already all around us, from
self-driving cars and drones to virtual assistants
and software that translate or help us to invest.
Microsoft is using AI in its Bingsearch engine
Microsoft doesn't own ChatGPT, nor the chatbot's founding company OpenAI.
However, the two companies have been partnered commercially since 2016, and
Microsoft continues to be the company's largest investor.
Simplifying Investment Advise:
Influencing Education Choice:
An Indicative Example for Shipping?
WEATHER ROUTING: Improve operational efficiency
by optimizingroute and speed profiles for any sea
passage.
The wider portfolio of weather routing, is usually
considering the right dataabout wind, wind waves and
swell, sea currents, water depth, tropical storms, as well
as certain important safety parameters in relation to the
concerned vessel (The app will choose on our behalf...)
Robots and Humanoids (Machines)?
Remember: It is just a system “behaving similar”
to humans (or in a kind of “predefined manner”?)
Machines?
Remember: It is just a system behaving similar
to humans (or in a kind of predefined manner?)
The NewShipping Paradigm:
IMO MASS Scale
Adapted from MSC 100/WP.8, IMO (2018).
Future Regulatory Developments?
The roadmap for a “goal-based” MASS Code has
been developed to be further implemented through
the work plan in the following MSC sessions:
Points to note:
The shipping industry is following a risk adverse
behaviour; it is more likely to follow a step-by-step
pace of change rather than a very abrupt one!
The regulatory discussion of Maritime Autonomous
Surface Ships (MASS) and the implementation
efforts of the E-Navigation Strategy by the IMO are
two indicative examples that shipping has already
entered the Era of Digitalization!
A certain level of disruption for Jobs and Skills!!!
Applications of Artificial Intelligenceand Robotics
will work together with humans and complement
their efforts (partners, not competitors)
Autonomous Vessels and AI?
AI can be defined as the simulation of human
intelligence processes by machines, especially
computer systems.
Indicative examples of AI include expert systems,
natural language processing, speech recognition and
machine vision.
Today, it is clear that the hardware element of sensors
on board contemporary ships has already exhausted
the room of further improvement; the use of advanced
software applications and utilisation of AI tools to
improve more the capabilities of the various systems
used to support the conduct of navigation seems can be
viewed as the best alternative way forward.
Autonomous Vessels and AI?
AI tools can pave the way towards autonomous
systems and eventually to unmanned ships.
In the not so distant future, humansand machines
will effectively collaborate together in the same working
environment
Image and/or Speech Recognition applications are
looking today as the most promising solutions; at the
same time, there still challenges that must be resolved!
RealAutonomous Vessels?
Systems that will be able to make decisions by
“themselves”, requiring no human input.
A very important example of this new/different operating
paradigm is “Image Recognition” (including optimization
of video processing); this way, existing sensors (such
as Radars/EOs or Sonars) will become “eyes and ears”!
Building, improving and running AI applications requires
immense computing power; a Cloud-based architecture
offers that in a flexible and scalable environment (at
relatively low-cost and without huge initial investments).
Big data is a prerequisite for AI and AI is the solution to
process unstructured data and derive insights from it.
What is the expected timeframe for “Autonomy”?
Why is the Shipping Industry hesitant towards AI?
Indicative Topics for Further Discussion:
... (3) Drones and Autonomous Underwater Vehicles (AUVs) are being developed to enhance monitoring and support hydrographic surveys (Johansson et al., 2023;Lajeunesse et al., 2011). (4) Big data analytics and artificial intelligence (AI) provide a wide range of opportunities in the Arctic (Bohlmann & Koller, 2020;Dalaklis et al., 2023b;Dalaklis, 2023) Examples are AI-ARC project based on AI technique (AI-ARC, 2022) and the SEDNA project which is developing sea ice forecasting products using big data analytics (CORDIS, 2022). (5) Other technologies invested to respond to safety issues include anti-icing solutions, icebreaking enhancement, oil spill response equipment, etc. ...
Article
Full-text available
The retreating ice coverage and reduced (ice) thickness scientifically recorded in the wider Arctic region, during the last few decades, are transforming it into a more accessible operating environment. Vessels engaged in maritime transport activities can now navigate the already established routes for more extended periods each year. With this background, Arctic shipping routes have attracted the interest of academics and maritime stakeholders because of the potential distance reduction compared to other existing (and often viewed as) conventional routes utilizing the Suez and Panama Canals today. However, the existing Arctic shipping environment requires specific future safety investments. This paper intends to provide input towards better-informed decisionmaking and identification of priority investments needed to improve the level of safety related to the Northern Sea Route (NSR) and Northwest Passage (NWP). A multi-attribute decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank the various proposed safety investments. The results indicate that “infrastructure and facility” should come first, followed by “personnel,” “technology,” “measure,” and “management” investments. Ice monitoring and weather forecasting, strengthening Arctic seafaring expertise, and icebreakers stand out as the top three most important future investments required in the region.
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