Distributed Intelligent Sensing in Wireless Sensor Networks

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




Exploration of an Incremental Suite of Microscopic Models for Acoustic Event Monitoring Using a Robotic Sensor Network

C. M. Cianci; J. Pugh; A. Martinoli 

2008. IEEE International Conference on Robotics and Automation, Pasadena, CA, US, May 19-23, 2008. p. 3290-3295. DOI : 10.1109/ROBOT.2008.4543712.


Toward Multi-Level Modeling of Robotic Sensor Networks: A Case Study in Acoustic Event Monitoring

C. M. Cianci; T. Lochmatter; J. Pugh; A. Martinoli 

2007. International Conference on Robot Communication and Coordination (ROBOCOMM), Athens, Greece, October 15-17, 2007. p. 1-8. DOI : 10.4108/ICST.ROBOCOMM2007.2275.


Threshold-based algorithms for power-aware load balancing in sensor networks

C. M. Cianci; V. Trifa; A. Martinoli 

2005. IEEE Swarm Intelligence Symposium (SIS2005), Pasadena, California, United States, June 8-10, 2005. p. 349-356. DOI : 10.1109/SIS.2005.1501642.