On the open ocean, identifying vessels can be challenging. Governments and maritime insurers use the Automatic Identification System (AIS) to identify ships, but bad actors can easily “go dark.” If a ship has deactivated its AIS beacons, there’s a chance it could be involved in smuggling, piracy, illegal fishing or human trafficking.
Hawkeye 360 is a data analytics company that aims to address this challenge using space-based radio frequency (RF) mapping. The six year-old company, headquartered in Herndon, Virginia, operates a constellation of commercial satellites to detect, characterize and geolocate a broad range of RF signals. It uses RF signals from sea to identify the characteristics and behavior of vessels. For instance, it evaluates vessels’ historical data and known interactions.
With its maritime RF data, Hawkeye 360 says it can predict whether a specific vessel is likely to engage in similar activity as sanctioned vessels — information that would be valuable for commercial maritime activity, national security operations, environmental protection and other use cases. The company developed these capabilities using Amazon Web Services’ SageMaker Autopilot, a fully-managed service for building, training and deploying machine learning models.
Using Autopilot, Hawkeye 360 is able to develop and deploy ML models twice as fast as it was previously. They plan to integrate the custom ML models into a variety of its products.
“RF signals can provide valuable insight into commercial vessel activity across the globe, even when bad actors seek to hide their location,” Tim Pavlick, HawkEye 360’s VP of product, said in a statement. “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.”
