The Maritime and Port Authority of Singapore (MPA) and IBM have jointly completed the pilot trial of three modules under the MPA-IBM SAFER project, which will be rolled out progressively beginning September 2017.
Project SAFER, derived from “Sense-making Analytics For Maritime Event Recognition,” is a collaboration between MPA and IBM to develop and test new analytics-based technologies, aimed at improving maritime and port operations to support increasing Singapore’s growth in vessel traffic.
Altogether, there are seven modules under Project SAFER which offer new capabilities for automating and increasing the accuracy of critical tasks that previously relied on human observation, reporting, very high frequency (VHF) communication, and data entry.
These seven modules include automated movement detection, infringement analytics, pilot boarding detection, bunkering analytics, prohibited area analytics, vessel traffic arrival prediction, utilization detection and prediction.
The pilot trial of the three modules that have been completed includes automated movement detection, infringement analytics and pilot boarding detection. The rest of the modules will be rolled out by January 2018, MPA said.
MPA’s Port Operations Control Centre (POCC) handles more than 1,000 vessel movements daily in Singapore’s port waters. One of the many roles of the vessel traffic management (VTM) officers is to enter the start and end time and location of a vessel into the port traffic management system whenever a ship master reports its movement over the radio system. Using cognitive and analytics technologies to detect and predict vessel movements, this module reduces radio communication between MPA control center and ship masters and eliminates the need to enter ship movement details by automatically detecting the start/end time and location of a vessel in real time. In addition, SAFER improves the accuracy of the information in movement time and location by up to 34%, as well as frees up VTM officers to carry out their other roles.
MPA’s port inspectors (PIs) keep the region’s waters safe by enforcing regulations on marine safety and environmental protection. They also coordinate and respond to any marine incidents in the port. Common infringements include operating in port waters without a valid permit or license, transponder-related infringements such as switching it off deliberately and speeding. Previously, PIs were guided by their intuition to look for suspicious activities rather than quantitative information when patrolling the waters. As a result, they may miss certain events of interest. With the machine learning based analytics and vessel prediction models developed for the SAFER system, PIs are able to detect suspicious or abnormal vessel behavior through alerts that are be sent them. This enables them to take a more targeted approach when conducting an inspection, hence improving efficiency of their daily routine, according to MPA.
MPA works closely with PSA Marine (PSAM) to ensure that 95 percent of vessels requiring pilotage service will be served within 15 minutes. Currently, MPA conducts audit checks when there is an appeal or dispute. This SAFER module enables MPA to automatically detect the pilot boarding time thus validating PSAM’s pilotage service level. The system will also facilitate dispute resolution, if any.
“We will continue to develop our digital strategies through the use of data analytics and machine learning technologies to optimise our port operations and enforcement to meet existing as well as future demands,” Andrew Tan, Chief Executive of MPA, said.
“The SAFER project will enable us to reap immediate benefits especially in the areas of next-generation port enforcement and monitoring of vessel movements,” he added.
“AI is transforming every industry and the marine domain is no exception. The SAFER solution is an example of how IBM’s AI research for business is supplementing and increasing human capacity by making our waterways and sea lanes safer and more efficient,” Robert Morris, Vice President, Global Labs, IBM Research, commented.
source; World Maritime News