Startup HawkEye 360 announced the development of new maritime security and vessel monitoring capabilities which will use small satellites to locate the source of commercial radio frequency emissions.
The solution will use geolocation services with a customized machine learning model developed through Amazon Web Services’ (AWS) Machine Learning (ML) Solutions Lab.
The capabilities will leverage underlying vessel characteristics and behavior to predict whether a given vessel is likely to engage in similar activity as sanctioned vessels
said HawkEye 360.
HawkEye 360 used Amazon SageMaker Autopilot to develop the purpose-built, proprietary algorithms undergirding the new capabilities. These algorithms can help generate deeper insights into RF data.
RF signals can provide valuable insight into commercial vessel activity across the globe, even when bad actors seek to hide their location. 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
said Tim Pavlick, Vice President of Product at HawkEye 360.
The new algorithms evaluate vessels’ historical data and known interactions, along 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, smuggling and more.
This RF signals analysis and machine learning ability can help make the oceans a safe place by supporting a variety of applications, including commercial maritime activity, national security operations, maritime domain awareness, environmental protection and more
HawkEye 360 concluded.
