Multi-sensor fusion platform for monitoring systems

A research group from Universidad Carlos III de Madrid (UC3M) has developed an advanced multi-sensor fusion platform for surveillance and monitoring systems. The technology integrates and unifies data from heterogeneous sensors within their operational context, providing enhanced situational awareness over large-scale areas. The solution is based on Artificial Intelligence techniques and advanced information fusion methods to support reliable detection and tracking.

The platform enables advanced multi-sensor fusion by combining data from radar, AIS, ADS-B, cameras, and contextual information, significantly improving surveillance performance in maritime, aerial, and coastal environments. It incorporates proprietary high-level algorithms for sensor alignment, data association, and non-linear estimation, including Interacting Multiple Model (IMM) approaches combined with computational intelligence to ensure adaptive and robust system behavior.

The architecture is modular and generic, allowing full configurability and straightforward deployment across diverse scenarios. Context-aware processing leverages geographic, dynamic, and operational information to optimize tracking accuracy and reduce false alarms and errors. A functional demonstrator has been validated using both real-world and simulated data, providing a solid basis for industrial-scale implementation.

Collaboration sought:
Technical Cooperation Agreements are sought with industrial partners interested in co-developing the multi-sensor fusion platform and integrating it into existing or new surveillance systems, particularly in the maritime and industrial aeronautics sectors.