Pronto uses artificial intelligence to make better predictions. Image Credit: Port of Rotterdam / Pronto
A self-learning computer system used by the Port of Rotterdam to predict vessel arrival times has expanded its abilities to understand which vessels are being bunkered.
Pronto, an application for standardised data exchange on port calls, is used by almost half of shipping companies, agents, terminals, and other nautical service providers in the port to plan, implement, and monitor their activities during a port call.
Key is that is uses artificial intelligence to make better predictions.
“Various factors influence a vessel’s arrival time,” says Arjen Leege, Senior Data Scientist at the Port of Rotterdam Authority.
“This includes the vessel type and cargo type, as well as the location, route, sailing speed and movements of other vessels in the vicinity. We have mapped out the most crucial parameters. During this process we sometimes dropped parameters or added new ones. For instance, it emerged that the number of times a vessel has already entered the Port of Rotterdam is also relevant.”
Data sources include AIS and the Port Authority databases, including vessel arrival times at the loading platform.
The system was also loaded with some 12,000 items of historical data, enabling it to learn to predict how much time a vessel needs to move from the loading platform to the berth.
Arjen Leege, Senior Data Scientist at the Port of Rotterdam Authority
The computer can also look further into the future and calculate the arrival times of vessels that are still some seven days away from the Port of Rotterdam
“Computers can make complex connections must faster than people,” explained Leege.
“We can now predict with 20-minute precision when arriving vessels will reach the berth. The computer can also look further into the future and calculate the arrival times of vessels that are still some seven days away from the Port of Rotterdam. By looking further ahead, we will ultimately be able to predict a vessel’s entire route. Perhaps even some 30 days in advance, including multiple ports.”
The Port says using artificial intelligence has already reduced vessel waiting times by 20% and it is now looking at other ways to apply the technology.
“The more details we know at an earlier stage, the better we can plan our resources. If you know it will be busy in the port you can, for instance, increase the towage capacity in advance by requesting tugboats from another port to call at Rotterdam,” says Leege.
"Pronto can now also identify which vessels are bunkered, piloted or towed in the port. Possibly there will be new applications in the future that we’ve not considered as yet. That is what’s great about this development."
While improving port efficiency is generally seen as a good thing, it can also put pressure on bunkering operations.
Maersk Oil Trading (MOT) this week said increasingly faster turnaround times were one of the reasons it decided to install a new mega-mass flow meter (MFM) in Singapore with double the flow capacity of typical systems.
“Our customers need large quantities of highly viscous fuel oil. However, as terminals become more efficient port stays are becoming shorter,” MOT said.