Safety at sea
Orca AI’s system allows maritime vessels to combine the accuracy of machine learning with the common sense approach of a real crew.
“But to achieve these different levels of autonomy we must think of the ship as an integrated system of systems,” Boylen adds. “It is not just about black-box navigation, but also about seamanship, vessel management, cargo management and the management of interactions with other vessels. And the key difference between an autonomous ship and a conventional vessel is that an autonomous ship must be able to act appropriately to protect itself, other marine users and the maritime environment in the absence of human intervention.”
“As [each of the parts of the supply chain] use more data, AI will be able to analyse this data and generate insights – both on board and the fleet level – translating into a safer, more efficient and sustainable industry.”
Dor Raviv Autonomy in action
A technology suite that includes AI will ultimately enable navigation to be both common and repeatable, removing the vagaries associated with human beings, which include fatigue, lack of skills and poor workload management. Nevertheless, autonomy introduces other challenges. “An array of sensor types – radar, cameras, LIDAR, AIS and others – combined with software including AI all have ambiguities that may contribute to uncertainty,” observes Boylen. “Akin to the automotive industry, the regulatory and assurance space become the critical enablers. The challenge is delivering a model that can evidentially demonstrate the safety of these solutions in a quantifiable fashion. We should recognise that autonomous cars are still not yet available for general use. “However, there is still a great deal of confusion around autonomy, and there are incorrect visions of robot ships plying the seas without human control,”
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he adds. “The opposite is true. People are at the core of autonomous shipping. We rely on our seafarers’ skills to bring their ships safely into port and this will be true whether they are actually on the ships or not.” One technology provider, Orca AI, has started to introduce AI systems for maritime vessels – notably cargo ships, ferries and tankers – to improve navigation and avoid accidents by reducing human error. Its co-founder and CTO, Dor Raviv, believes the technology will transform a very traditional industry. “We are doing this by providing crews with unique insight, such as alerting them to dangerous targets, prioritising risk in real time and assisting with complex navigation situations,” he remarks. “This way, we enable crews to learn how their ships behave in terms of safety parameters, as well as giving them an understanding of specific areas around the world in order for them to make informed decisions when they navigate them.” The key factor is the analysis of data to make the job of the watchkeeper easier. “AI and automation can reduce the workload of the watchkeeper, whose job is to continuously monitor and alert on risks around the vessel, which is tedious, repetitive work,” Raviv explains. “AI, on the other hand, doesn’t get tired and never misses important information.
“The hardest use case for watchkeeping is when there are many targets surrounding the vessel,” he adds. “It’s hard to understand who is performing [the] action that could affect the safety of the ship, and AI excels in these congested areas with its ability to process multiple data points simultaneously.” The company’s Orca AI O1 solution automatically detects, prioritises and alerts on-board crews to maritime targets in real time. It is used by some of the biggest actors in the industry, among them MSC, Maran Tankers and TMS Gas. The system integrates with all existing navigation systems on board and adds context to them via computer visualisation algorithms.
The system also continuously gathers risk data from the entire fleet and uses machine learning to
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Orca AI
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