The Best Insights Come From Combining Data With Personal Experience



Patrick Brehmer, Senior Manager, Applied Innovation, Navis


Examples of artificial intelligence / machine learning (ai/ml) aided decision making in container terminal planning processes.

Some people believe that planning for the future is a waste of time, as unforeseen events and dynamics at play will impact any attempt at accuracy. While this may feel like the case in our personal lives – think of the Covid-19 pandemic – this may not be entirely true for container terminals.

In this paper, we will share examples of how predictive visibility can become a part of everyday planning processes and support expert users to make even better decisions. Container terminals are dynamic environments and operators face a variety of planning and optimization challenges.

In our work with planning and execution teams, we have seen the importance of automation and use of advanced equipment optimization solutions to enable improved results, better safety, as well as improved user experience. And now, with the use of artificial intelligence and machine learning techniques (AI/ML), cloud technology and terminal operating system (TOS) data, we foresee a wave of innovation approaching with many different use cases that can be addressed.

We want to share our insights on two specific use cases we have been working on.

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