May 23, 2017

The ecosystem for autonomous maritime transport

Matti Vakkuri

Head of technology, Industrial Internet, Tieto

Autonomous vehicles are a global phenomenon, and the field has taken huge leaps forward in the past 15 years. If a decade ago someone told me that we’d have cars with true self-driving capabilities in 2015, it would have been very hard for me to believe.

Even though the regulations in the field are still lagging behind, the technology for autonomous vehicles is somewhat ready. Large contributors to autonomous vehicles were the development of signal processing technology and visual analytics. In addition, some important innovations and trends started to emerge after the turn of the millennium, such as big data around 2005 – not to forget the Internet of Things. Both gave a new opportunity for artificial intelligence.

Gladly, back in 2013, Tieto and I were given an opportunity to lead DIMECC’s Data to Intelligence program, which is the largest big data research program in Finland until today. Through the program, we were able the get a comprehensive view in the development and the future potential of the latest technologies in big data, algorithms, machine learning, deep learning, and artificial intelligence. Among tangible research and innovation results of the program, the best outcomes were the new kind of understanding of the value of pre-competitive research and the power of co-creation, both of which are in use in the autonomous maritime ecosystem.

Autonomous shipping – the reality in 2025

Now, when autonomous cars are already reality, why not explore the possibilities in the skies or on sea? Around a year ago, the idea was introduced to me with a sales pitch claiming that an autonomous maritime ecosystem will be reality in 2025. At that point, the planning of this autonomous system had already been started, and Tieto was invited to take part in the bold and challenging journey to make it really happen.

The project is not aiming only to transform the navigation of boats from locally to remotely controlled and then finally to completely autonomous – the plan is to transform the whole maritime industry, and further on the whole logistics chain, through digitalization. Therefore, new business models and innovations are required.

Collaboration between different players in the market

We will face several obstacles on our journey – or challenges, as I’d rather call them. In practice, we need to work together to tackle these challenges. We need to utilize the results of existing academic research and emphasize collaboration between universities and companies – not to forget intercompany cooperation. We need trends like digitalization, connectivity, automation, electronic systems, analytics, and optimization to tackle issues like emissions reduction and boost the work ahead.

The whole task of having autonomous ships sailing safely and in an optimized way is so immense that there is work for a huge number of different players in the market. In this ecosystem of different partners, I see Tieto as an integrator of big data, IoT, analytics, artificial intelligence, cyber security, and several business domain areas. We also warmly welcome new parties to work with the ecosystem to make this common dream come true.

Autonomous maritime transport and Tieto’s data driven strategy go hand in hand

As I see it, we need new ways of working and new methods of collaboration in various ecosystems. This translates into cross-discipline research in universities and cross-industry collaboration on the business side. Our journey from locally to remotely controlled and then autonomous operations will involve expertise outside the maritime field: wellbeing and intelligent buildings are good examples. 

Tieto’s broad national and international research collaboration helps the whole autonomous maritime ecosystem to benefit fully from the existing research and development in algorithms, machine learning, deep learning, and artificial intelligence. In the end, it all comes down to creating information from data and knowledge from information – and learning how to utilize the knowledge in the best way possible.

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