HullSight Ultimate: Automated Biofouling Analysis

Your Strategic Foundation for Data-Driven Fleet Operations

HullSight Ultimate delivers immediate operational benefits while establishing the digital foundation for future fleet optimization. The cloud-based system transforms underwater hull inspection videos into standardized, objective biofouling assessments through advanced computer vision technology, providing reliable reports today that replace inconsistent manual assessments. Simultaneously, the standardized digital data collection creates the foundation for predictive maintenance, fuel consumption optimization, and fleet-wide performance analytics that will drive operational efficiency in the years ahead.

What is HullSight Ultimate?

HullSight Ultimate is a cloud-based solution for automated processing of underwater hull inspection videos. During inspections, videos are captured from different sections of the ship hull. The data is then uploaded to the system, where images are automatically extracted from the videos to ensure the inspected area is covered completely. The advanced computer vision engine analyzes the amount and type of biofouling attached to the surface. With a single click, you can generate a standardized biofouling report or export data in structured formats for integration with existing maintenance management systems.

Learn more about our partner Blue Atlas Robotics.

Your Benefits

Consistent Data – Get a clear, objective analysis of large hull areas with AI-powered insights.
Speed-up Your Inspection – From automatic video analysis to inspection report in a few steps
Strategic Foundation – Combine hull condition data with performance metrics to optimize long-term vessel efficiency.

Digital Foundation for Predictive Analysis

Collecting detailed, standardized biofouling status data is the essential prerequisite for advanced predictive maintenance scenarios. The systematic documentation of hull conditions over time creates the data foundation necessary for developing predictive models that can forecast fuel consumption impacts, optimize cleaning schedules based on biofouling progression patterns, and enable fleet-wide performance benchmarking. Without consistent, quantified biofouling assessments, these predictive capabilities remain impossible to achieve reliably.

Sample Output

Example of the Base Model that distinguishes clean structure, slime, soft fouling, and hard fouling. The background is not taken into account for calculating the percentages.