The Port of Dover needed to manage highly variable freight traffic flows, with limited visibility of incoming volumes and congestion risks.
Unpredictable arrivals and external factors (e.g. incidents, weather) created bottlenecks, reducing operational efficiency and increasing disruption across the network.
Entopy deployed its AI-enabled digital twin platform, combining real-time data with predictive micromodels to forecast freight arrivals and traffic conditions.
The platform provided forward-looking intelligence on volumes and congestion, enabling operators to proactively allocate resources and manage flow.
Entopy’s micromodel architecture chains together discrete models, integrating real-time, event-based data, such as accidents, weather, and network disruptions, to create a continuously adapting traffic model.
This enables dynamic, network-wide forecasting of congestion and freight flows, even under disruption.
Entopy is the always-on intelligence layer that helps complex operations anticipate consequence and act earlier.
