Maritime Data Analytics

Powerful algorithms feeding on different types of data sources that improve the business intelligence at the port, enhancing the planning department efficiency with machine learning methods towards port digitalisation.


The Maritime Data Analytics (MDA) is an ICT toolset based on powerful algorithms feeding on different types of data sources (AIS, FAL forms and smart cameras) that improve the business intelligence at the port from the traffic at the sea (enhancing ETA/ETD and other optimizations of vessel traffic and manouvering) and on the road (forecasting and avoiding congestion at the port gate and throughout the city using better the parking availability) with machine learning methods.

Uses the vessel calls, the machinery available and the chain of operations for each cargo (supply chain), prioritises them and distributes the machinery operations across time.

Schema of the product:


1. Allows for further insight on the operations held in the overall maritime ecosystem around the port and on the road to the port.

1. Improves the capacity of planning of port operators, business operators and policy makers to reach economic growth and to reduce the environmental impact.

2. Allows to compare economic and environmental time impacts of different transport mode improving the planning of port transport operations monitoring the environmental impacts.

2. Utilizes sophisticated algorithms to forecast ETA/ETD, helping to plan arrival/departure times to minimize congestion at the port, optimising costs/gains.

3. Can support a shared planning of freight transport with business operators in order to reduce the impact on hinterland and environment.

3. Reduce the congestion events in the Port area and of the hinterland, by an interoperability with other Regional node.

Keywords: intermodal transport, traffic optimization, multimodality, queue conjestion prevention, predictive algorithms, data insights, machine learning, ETA, ETD, AIS.