Written by: Dr Anna – Mari Antoniou
Senior Lecturer in Maritime and Commercial Law University of Brighton
The answer to that depends on understanding the relationship between the technology and the unique characteristics of the industry. There is a mass of quantitative and qualitative data that can be harnessed and utilised through artificial intelligence systems (AI) which can make individual maritime companies and the industry, more effective and more efficient. From ship building and design through to ocean risk analytics and collision avoidance, AI can be a positive development for the industry if harnessed correctly.
Smart technology can bring together the propulsion, manoeuvring and communication systems and the data they have been collecting to give the captain and officers a consolidated overview of the entire operation of the vessel
What is AI?
AI at its core, is one area of computer science where the aim is for the machine to function like a human brain. Although first discovered in 1956 by John McCarthy, it didn’t really start to mature until after the 1980s. A key part of AI for the maritime industry is machine learning; giving the computers access to big data from which they can extract information and then solve problems. It is in the last 40 years or so where this data gathering has been possible on a large scale and only in the last decade where it has effectively exploded. According to the US AI platform provider SparkCognition, 90%
of all data has been created in the last couple of years. Now is the time we really see possible applications of AI in the shipping industry.
There are so many AI based platforms providing solutions for maritime companies that they cannot be listed here. What one can say, is that they do range from across all areas of the industry and are based across the world. In essence, AI is everywhere and one does have to wonder, if, after an appropriate risk and cost analysis is conducted, the conclusion is that the voyage from point A to point B is faster, safer and cheaper, it is a solution worth considering?
How can companies use it?
When one considers harnessing useful data, filtering it and using it to improve the safety, speed and cost of an international transportation system, one of the first places to contemplate implementing AI is through an integrated control system. Smart technology can bring together the propulsion, manoeuvring and communication systems and the data they have been collecting to give the captain and officers a consolidated overview of the entire operation of the vessel. This can be used to monitor and improve vessel performance but can also be used to filter real-time route information that could be implemented immediately to, for example, make sure the vessel accurately stays on course without human input, or better control the speed and angle of the vessel to optimise the route. Collision avoidance is a close link here – again smart technology can use data generated by cameras and alarms to create real-time awareness of nearby hazards so that collision danger is decreased. Concerns surrounding the health of our oceans can also be aided by AI. Not only will collision avoidance systems avoid environmental damage, there are AI systems dealing with ocean risk analytics; specialised software that can identify abnormal oceanic events to evaluate marine threats. AI can also help optimise cargo distribution on a vessel and bay arrangements – this is called digital cargo. Digital optimization technology considers a variety of factors affecting stowage for example, size, weight, destination and priority speed of a container, giving companies the opportunity to optimise cargo placement across the vessel. This can also streamline the process at ports reducing terminal traffic. On average, 30-40% of ship capacity is empty space but with digital cargo optimization this can be reduced to below 15-20%. Even ship design and construction can be aided using AI by analysing data related to the wind, weather and ocean currents as well as ports and shipyards integrating AI-based predictive analytics in their systems to manage the increasing volume of ship traffic.
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