We are applying principles of distributed intelligence and model-based methods of distributed control and analysis to (potentially mobile) sensor networks, particularly for event-driven monitoring scenarios (where the quantity being measured or affected is spatially and temporally unpredictable) and deployments requiring relatively high sampling rates (where simply enforcing a < 1% duty cycle is insufficient or ineffectual). Areas of special interest include acoustic monitoring, power management, collective attention, dynamic re-configuration, and collaborative signal processing using adaptation and learning at the level of the individual.
Leveraging the Swarm-Intelligent Systems Group’s accumulated expertise in system design and systematic experimentation with mobile robotic swarms, this project attempts to bring the rigor of reproducible experiments and multi-level modeling to the domain of sensor and actuator networks.
Team and Collaborators
In collaboration with:
Sponsors and Research Period