Global Spatial Technology Solutions has been selected by the Canadian Space Agency to develop an advanced AI prediction capability for identifying and preventing maritime risks like vessel collisions, groundings and illegal activity.
“This capability will incorporate data fusion of current and future satellite data sets along with environmental data and apply the power of machine learning to satisfy unique user needs,” the Dartmouth company said in a news release Tuesday.
With thousands of vessels moving through Exclusive Economic Zones on a daily basis, GSTS says, governments are challenged with sifting through massive amounts of data to characterize behaviour. GSTS's prediction capability will augment operator decision-making by delivering actionable intelligence in near real time, according to the release.
"This capability will enable GSTS to expand our growing AI solutions by fusing current and next-generation satellite data sets, enabling game-changing results," said Richard Kolacz, GSTS CEO, in the release.
"Real-time data fusion from multiple sources will enhance decision-making in the maritime sector in areas such as reducing emissions, preventing collisions and groundings, and detecting illegal activities, including illegal fishing and embargo running.
“It is a further step in GSTS's development and rollout of a global vessel management system to support safety, security and environmental protection in the maritime sector."
GSTS says the project will strengthen and expand upon its AI service offering for the maritime sector through the OCIANA platform. OCIANA is an AI platform that integrates and processes space and terrestrial data sets related to ocean, weather and marine activity, providing real-time decision-making information for the maritime sector.
The project is undertaken with the financial support of the Canadian Space Agency through the smartEarth Program.
GSTS bills itself as providing artificial intelligence products for the maritime sector, for civil, commercial and security agencies and industries.