HawkEye 360 have developed maritime security and vessel monitoring capabilities using AWS’ machine learning. Credit: JF Martin on Unsplash.

HawkEye 360 has developed new maritime security and vessel monitoring capabilities that combine its radio frequency (RF) geolocation services with Amazon Web Services’ (AWS) machine learning (ML) model.

The maritime security and vessel monitoring capabilities will be integrated into the HawkEye 360 portfolio of products.

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Using underlying vessel characteristics and behaviours, it becomes possible to predict whether a given vessel is likely to engage in similar activities as sanctioned vessels.

Amazon SageMaker Autopilot, a fully managed service that helps to quickly build, train and deploy ML models, has been used by HawkEye 360 in the development of the algorithms undergirding the new capabilities.

The purpose-built, proprietary algorithms can help to derive maritime domain insights from RF and vessel information.

HawkEye 360 stated that the RF signals ability and ML analysis support a range of applications such as commercial maritime activity, national security operations, maritime domain awareness and environmental protection.

HawkEye 360 product vice-president Tim Pavlick said: “RF signals can provide valuable insight into commercial vessel activity across the globe, even when bad actors seek to hide their location.

“With these ML-backed capabilities, we will empower customers to cut through an ocean full of noise to obtain more timely and critical insights from maritime RF data to improve mission outcomes and prevent illegal and illicit activities.”

The algorithms evaluate past data, known interactions and contextual vessel characteristics to produce insights into the complex connections that are involved in illegal maritime vessel activities, such as illegal fishing, human trafficking and more.