Cognitive Systems and Robotics
The emergence of networked embedded systems and sensor/actuator networks has made possible the collection of large amount of real-time data about a monitored environment. In many cases the collected data may be incomplete, or it may not make sense, thus compromising the sensor-environment interaction and possibly affecting the ability to manage and control key variables of the environment. The main objective of iSense is to develop intelligent data processing methods for analyzing and interpreting the data such that faults are detected (and where possible anticipated), isolated and identified as soon as possible, and accommodated for in future decisions or actuator actions. This project will focus on cognitive system approaches that can learn characteristics of the monitored environment and can adapt their behavior and predict missing or inconsistent data to achieve fault tolerant monitoring and control.
Call for proposal
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