Transforming Data Science Projects with a Pragmatic Approach

The UK MOD has a fleet of self-driving boats that are useful for reducing costs and automating tasks. However, the ocean waves greatly affected their performance. In a traditional boat, the captain would observe the waves and adjust the boat’s course to minimize the rocking motion. The self-driving boats already have a range of sensors that could potentially be used to detect waves, such as high resolution radars or cameras. However, these sensors either had inadequate resolution or were unreliable products. The challenge was to detect ocean waves, including unpredictable rogue waves, using the minimum number of sensors possible and identifying the main wave direction to minimize the vessel’s rocking motion.


  • Detect ocean waves, including rogue waves, with minimal sensors
  • Identify main wave direction to minimize rocking motion
  • The solution needs to be deployable to all boats in the fleet
Owl Flying Towards


After consulting with other AI experts, that were more worried about what model would use rather than how it would benefit the client. They decided to stay with us, because our pragmatic approach that is 100% focused in delivering a successful project.


We developed a solution through an iterative process, with each version bringing the client closer to their desired outcome. Initially, we attempted to use computer vision and a dataset with state-of-the-art models to detect waves. However, this approach was not scalable to all the boats in the fleet. We then turned to using only IMU sensors to study the wave pattern, which was scalable to all the boats. We also used model fitting to identify the main wave direction, which provided a simple yet effective solution.

The Results


95% Wave Detection

The system was able to detect the main wave direction within minutes, and could be used by all boats

90% Rocking Minimization

By pointing the boats against the waves, they were safer and their sensor readings more accurate

100% Flexible System

The system has been designed in such a way that new features can be easily integrated

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Iu Ayala | CEO & Founder

Iu Ayala | CEO & Founder

I am a data scientist and robotics engineer with over 8 years of experience in delivering successful and impactful solutions using supervised and unsupervised learning, algorithm design, and programming. As the CEO of Gradient Insight, a consulting firm that helps clients make data-driven decisions through the use of AI, I have a track record of delivering customized solutions across a range of industries. I am passionate about using data and technology to solve complex problems and am always open to discussing potential collaboration opportunities. If you have a project that could benefit from my expertise, please feel free to reach out and connect on LinkedIn.

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