BAE Systems aims to develop machine learning analytics as a service – a first-of-its-kind, cloud-based model for the government – that can leverage commercial and open source data to deliver constant worldwide situational awareness for a diverse range of challenges.
BAE Systems was awarded a contract by the US Defense Advanced Research Projects Agency (DARPA) to develop the new technology model, which seeks to provide an automated service to leverage commercial and open source data, including satellite imagery, to deliver continuous worldwide situational awareness for a diverse range of challenges, including anomaly detection and prediction.
As part of DARPA’s Geospatial Cloud Analytics (GCA) program, the BAE Systems FAST Labs research and development team aims to use the company’s Multi-INT Analytics for Pattern Learning & Exploitation (MAPLE) technology to offer MAPLE as a service (MaaS).
This approach seeks to apply automated analytics to a problem, freeing operators to query the data to answer specific questions about important mission issues at hand while removing the traditional need to conduct extensive manual analysis.
For the purposes of this program, the BAE Systems team says it is seeking to apply MaaS to a proposed maritime challenge to automatically and reliably detect vessels that are engaging in illegal fishing.
The ultimate goal is to automate analytics in a new way so that machine learning can be used to discover nuanced patterns in both sparse and large data volumes to solve complicated security problems.