In a container terminal in the Port of Hamburg, an intelligent SimCog prediction enables better use of space, shorter transport routes and faster provision of containers for onward transport.
For the development of the basic algorithm, the historical container attributes, the goods data as well as the storage data of the containers are reviewed by SimCog Technologies and fused with external data, such as holiday seasons
Based on machine learning, a self-teaching algorithm is created that recognizes patterns in historical data
This algorithm is able to predict, already at unloading, when which container will be picked up in what order by which mode of transport
The algorithm of SimCog Technologies makes it possible to predict, already at the time of unloading, when which container will be picked up by which mode of transport.
Containers can thus be placed in the best possible location for temporary storage.
Containers stacked on top of each other need to be rearranged less often in order to load a container destined for onward transport.
More efficient positioning of containers allows more containers to be placed on top of each other in a meaningful way.
We will be happy to provide you with further details.
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