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Green Ports Toolkit
Global · Case study

Port of Rotterdam

Rotterdam, NetherlandsNot specified

A well-documented example of digital operations and decision support systems is the Port of Rotterdam’s digital twin and analytics environment in the Netherlands. This case shows how a large, complex port uses data, models and dashboards in daily operations and, through separate data-informed initiatives, in long-term planning.

Location and Timeline

The Port of Rotterdam is Europe’s largest seaport, with about 12,500 hectares of port area, land and water. Around 2017-2018, the Port of Rotterdam Authority began a major digital-transformation program with partners such as IBM, Esri and Cisco, aiming to create a port-wide “digital twin” that combines real-time data from ships, infrastructure and the environment. (Geospatial Resource Platform, n.d.)

System Description and Purpose

The digital twin integrates multiple data streams: infrastructure, ship movements, weather conditions and hydro information, with sensors that report the state of assets in real time. (Port of Rotterdam, 2022)

On the operational side, harbor masters and traffic controllers use dashboards to:

  • Monitor vessel traffic density, approach routes and berth occupancy in real time
  • Assess how weather and currents affect nautical accessibility and safe under-keel clearance.
  • Predict waiting times and optimize berthing windows, reducing “sail fast, then wait” behavior. (Michael Keegan, 2019)

This supports just-in-time arrivals, smoother pilotage and tug allocation, and faster incident response when conditions deteriorate.

Separately from the operational digital twin, the port uses data and models in several distinct planning initiatives, for example:

  • Shore power rollout: the Shore Power Strategy 2025-2035 uses historical data on vessels calling at Rotterdam to estimate that shore power could avoid about 500 kilotonnes of CO2 a year, and focuses on vessel segments with relatively high emissions. (Port of Rotterdam Authority and Municipality of Rotterdam, 2025)
  • Climate adaptation: the port's adaptation strategy, finalized in 2021-2022, uses flood modelling and working assumptions of 35 cm sea level rise by 2050 and 85 cm by 2100 to plan prevention, spatial adaptation and crisis management measures (Climate-ADAPT, 2025)
  • Energy transition: a digital twin of the port's energy system, built by Gradyent at the request of the Port Authority as a proof of value, models how electricity, steam, hydrogen and offshore wind interact across the industrial cluster. (Port of Rotterdam, 2025)

Cost and benefits

Public sources do not give a single project cost. The Port Authority attributed a 20% reduction in average vessel waiting time to its "Pronto" port call optimization app (Wee, 2018). In 2020, the IBM digital twin program expected that shipping companies and the port could save up to one hour in berthing time, worth about USD 80,000 (Henderson, 2020); this is an expectation, not a measured saving.

Transferability

DMC ports do not need a full port-wide digital twin to benefit from this approach. They can start by bringing vessel movements, berth occupancy and weather data into one shared dashboard for harbor masters and traffic controllers. Even simple predictions of waiting times and berthing windows can reduce "sail fast, then wait" behavior. Planning uses, such as shore power or flood modeling, can be added later as separate data-informed studies.