Relocatable Multi-Sensor System
Description
Border security, detection of Small Unmanned Aircraft Systems (SUAS), and multi-sensor fusion.
Detailed example
The outputs include real-time data identifying and categorizing potential items of interests, while filtering out false or non-relevant items of interest like animals. These outputs are used to provide situational awareness and support decision-making for CBP personnel.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The system uses advanced sensor technology to differentiate valid items of interest (IOI), such as unmanned aircraft systems and humans, from other detections such as animals or other environmental objects. By integrating radar and other sensor data, the system filters out false alarms, ensuring more accurate identification of potential IOI. This capability enhances CBP's ability to focus on legitimate risks while minimizing the time spent on non-threatening activities, improving operational efficiency at border and security checkpoints.
Audit / financial statement impact
Sensors and CUAS capabilities to support significant events. The AI combines sensor data from RF detections / radar/ and infrared / electro optical cameras. It combines all feeds and provides detections on the user interface back to users. Fully standalone and airgapped system. Looking to identify non-RF drones. System does not have any mitigation capability, system cannot autonomously mitigate an aircraft, it only detects and provides a digital track on the GUI/map for further user investigation. This use of AI does not serve as a principal basis for decision or action.
Controls / human review
ATO: Not reported; PIA: Not published