Amazon is providing maritime security and vessel monitoring solutions to governments and commercial organisations
HawkEye 360 is using formation-flying satellites, radio frequency (RF) geolocation technology and customised machine learning algorithms from Amazon Web Services (AWS) to monitor vessels for safety and security services.
“RF signals can provide valuable insight into commercial vessel activity across the globe, even when some seek to hide their location,” said HawkEye 360 vice president of products Tim Pavlick. “With these machine learning-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,” he said.
US-headquartered HawkEye 360 used Amazon SageMaker Autopilot to build, train and deploy machine learning models. It developed proprietary algorithms to generate deeper insights into RF data in half the time than was previously possible, evaluating a vessel’s historical data and known interactions.
This is linked with contextual vessel characteristics to generate insights into the complex connections involved in illicit maritime vessel activity, such as illegal fishing, human trafficking, ship-to-ship transfer of illegal goods and smuggling.
Machine learning provides analysts with a holistic view of maritime activity and the ability to detect, predict and zoom in on high-risk activity.
Amazon senior manager for machine learning solutions Sri Elaprolu said machine learning models are solving problems identified within the world’s oceans.
“By combining HawkEye’s data and deep domain expertise with Amazon SageMaker Autopilot, HawkEye 360 is able to halve the time for machine learning model development and deployment,” he said. “That frees up time for data scientists to focus on creating new and innovative solutions to the world’s problems.”
In February, HawkEye 360 launched its Mission Space platform, combining RF data and analytics for a holistic picture of worldwide RF activity, enabling analysts to identify trends and patterns with indepth detail from RF signals.
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