Analysis from Orca AI, creator of the world’s first automated situational awareness platform, has revealed the significant gains delivered by its platform for customers in the last 12 months. These include reducing the number of potential incidents and collisions, as well as increasing operational efficiencies to deliver both fuel cost and CO2 emissions savings.
The analysis was conducted on 110 commercial vessels, spanning tankers, containers, bulkers and Ro-Ro vessels, which were equipped with the Orca AI platform throughout 2022.
Orca AI calculated that during this period, its customers saw a 26.9% reduction in the number of close encounter events, a 21.6% decline in sharp manoeuvres, and an 18% reduction in extreme drops of speed.
According to Orca AI, these improvements in operational efficiency led to a 66,300 tonne reduction in CO2 emissions in total, helping customers to meet their sustainability goals as well as ensuring compliance in line with new CII regulations.
“Orca AI was founded with a fundamental commitment to help create a safer, more efficient and sustainable shipping industry,” said Dor Raviv, CTO and Co-founder of Orca AI.
“The impressive numbers are a result of our cutting-edge technology, and a close collaboration with our innovative and forward-thinking customers. The learnings from data collected by our platform helped our customers to adjust their companies’ safety policies and navigation-related operations and processes.
“The masters, officers and fleet managers we worked with quickly realised that Orca AI generates a real, tangible impact, and helps to mitigate the associated costs of safety incidents, downtime and reputational damage.”
The safety analysis was conducted on 10 million nautical miles of data collected in open waters by ships using the Orca AI platform. On average, each vessel experienced three close encounter events per 1,000 nautical miles sailed. Each close encounter event was analysed with various KPIs including the closest point of approach, time to closest point of approach, reaction time, average speed over ground, average cross-track error and weather conditions.