Signal Processing and Inference
Cyber Physical Systems combine a plethora of data from multiple sensors, robots and people. Different sources of noise in the sensor data make the tasks of signal processing, inference and learning particularly challenging. This activity encompasses a number of algorithms for denoising, sensor fusion, cross modality training and pattern recognition in sensor data. Applications range from activity detection and wellness monitoring to identification and authentication systems.
Head of Activity
The Cougar Project: A Work−In−Progress Report
Alan Demers‚ Johannes Gehrke‚ Rajmohan Rajaraman‚ Niki Trigoni and Yong Yao.
In ACM SIGMOD Record. Vol. 34. No. 4. December, 2003.
Energy−Efficient Data Management for Sensor Networks: A Work−In−Progress Report
Alan Demers‚ Johannes Gehrke‚ Rajmohan Rajaraman‚ Niki Trigoni and Yong Yao
In 2nd IEEE Upstate New York Workshop on Sensor Networks. 2003.
Hybrid Push−Pull Query Processing for Sensor Networks
Niki Trigoni‚ Yong Yao‚ Alan Demers‚ Johannes Gehrke and Rajmohan Rajaraman
In GI Workshop on Sensor Networks (WSN). 2004.