Ubiquitous sensors vs fast-moving adversaries. The race is on.
Gaining advantage by managing and exploiting complexity
Sentient Systems ensure that the right data is collected by the right sensors at the right time. These systems are core to the success of the future Intelligence, Surveillance, and Reconnaissance (ISR) activities.
This means fusing data from multiple sensors, tasking sensors to fill gaps and refine understanding, and pushing computation to the edge to reduce bandwidth requirements and accelerate our responses.
Boston Fusion develops and applies state-of-the-art data processing and machine learning algorithms to process and fuse data from multiple sensors, exploit multiple physics and non-physics based sensors, and leverage context to focus data collection. Our systems learn patterns of normal behavior (i.e. “patterns of life”), predict future activities and detect anomalies that might indicate changes in adversarial operations.
Our methods can exploit uncertainty information to better characterize the signal, provide enhanced clutter suppression to boost information, and determine the most salient features in multi-dimensional data.