Eniram Blog

Many companies in the shipping industry have already started their digital journey by automating data collection from their vessels. This connected mode of operations introduces a new level of transparency to onboard operations, but also has a downside - namely the ever-increasing amounts of information produced that is far beyond the capacity of any single person to process.
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Fully autonomous operation means that data collection, analysis, and decision-making and implementation are all automated and driven by artificial intelligence. The level of autonomy granted is going to be the key variable as we move towards this goal, but essentially autonomous operations change the human role from active operator to supervisor.
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A digital twin of a vessel can be used to demonstrate the added value of automatic data processing and machine learning. Once a digital twin model is in place, performance diagnostics and breakdown or simulation of future voyage configurations can be done without physical testing in specific conditions.
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AIS data can provide vessel owners/operators with a cost-effective way of tracking their fleet, planning and optimizing their voyages and improving the transparency of noon reports. For organizations in the Traditional phase, exploiting the possibilities presented by AIS data can be a risk-managed and cost-effective first step in the digital journey. 
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By outsourcing the data processing and analysis to an analytics company using digital twins, you can concentrate on putting the insights they provide into practice. Understanding the lifecycle of a digital twin will help you defining the capabilities you require from an analytics company.
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