Miscalculating when a vessel is due to arrive in port can result in significant delays, disruptions, and impact heavily on logistical operations. The new tool, the Sinay Hub, is a data-driven digital tool that uses AI algorithms to bring together all required data in one place.
The software is currently in use by one of France’s ports on the Northwest coast, with initial trials producing a 25 per cent improvement in the prediction of vessel arrival times.
Using data obtained from a ship’s AIS (Automatic Identification System), with historic voyage data, tidal patterns, and other data, Sinay can accurately predict when a vessel is due to arrive in port. This helps ports to optimise their efficiency, manage their logistical operations, and improve their competitiveness.
Monitoring air, water, and noise quality is another key responsibility for ports. The Sinay Hub has several modules which monitor, predict, and prevent pollution in real-time, replacing cumbersome manual data systems and further improving a port’s operational efficiencies as well as observing any environmental impacts.
“The Sinay Hub provides ports and the maritime sector with a 360° view of all their activities under one umbrella. From their own dashboard, the user can quickly and easily monitor, analyze and make decisions across their operations in real-time: predicting more accurately a container ship’s arrival into port, identifying problems relating to water or air quality, or noise pollution. This enables ports to be much more efficient in their operations and meet any environmental obligations,” explained David Lelouvier, managing director at Sinay.
“Recently, we completed the installation of the Sinay Hub at a major port in France, which manages over 2 million TEU in containership traffic. Since the Estimated Time of Arrival module (ETA) went live, the Sinay solution is proving to be more accurate than the previous data by achieving an accuracy level of 75 per cent versus 50 per cent. For 50 per cent of the time the Sinay data was more accurate than that supplied by ship’s captain, for 25 per cent of the time it was on par and for the remaining 25 per cent it was less accurate. However, with further modifications of the system which are ongoing, we are confident that very soon we can achieve accuracy of 90 per cent. These results prove that it is possible to harness big data to make significant improvements in a port’s operational efficiency.”