Signal Processing and Communications for Sensor Networks April 2, 2009

Favorite:

Google Tech Talks
April 1, 2009

ABSTRACT

Presented by Martin Vetterli

A sensor network is a spatio-temporal sampling device with a wireless communications infrastructure. In this talk, after a short overview of the Center on Mobile Information and Communication Systems, where large scale ad hoc and sensor networks are being studied, we will address the following questions related to large sensor networks and their applications in environmental monitoring.

1. The spatio-temporal structure of distributed signals, with an emphasis on the physics behind the signals, and results on sampling.

2. The interaction of distributed source compression and transmission, with a particular focus on joint source-channel coding. This is the key theoretical question in sensor network signal acquisition and communication.

3. Applications in environmental monitoring, like for example tomographic measurements, and a description of a large scale environmental monitoring project in the Swiss Alps. This project, called SensorScope , has generated large and novel data sets for environmental questions, all available in open access.

This is joint work with T.Ajdler, G.Barrenetxea, H.Dubois-Ferriere, F.Ingelrest, R.Konsbruck (EPFL), and M.Gastpar (UC Berkeley). The work is sponsored by the Center on Mobile Information and Communication Systems (http://www.mics.org), funded by the Swiss National Science Foundation.

Martin Vetterli received the Dipl. El.-Ing. degree from ETH Zurich (ETHZ), Switzerland, in 1981, the MS degree from Stanford University in 1982, and the Doctorat ès Sciences degree from EPF Lausanne (EPFL), Switzerland, in 1986. He was a Research Assistant at Stanford and EPFL, and has worked for Siemens and AT&T Bell Laboratories. In 1986, he joined Columbia University in New York, where he was last an Associate Professor of Electrical Engineering and co-director of the Image and Advanced Television Laboratory. In 1993, he joined the University of California at Berkeley, where he was a Professor in the Department of Electrical Engineering and Computer Sciences until 1997, and now holds an Adjunct Professor position. Since 1995, he is a Professor of Communication Systems at EPF Lausanne, Switzerland, where he chaired the Communications Systems Division (1996/97), and heads the Audiovisual Communications Laboratory. From 2001 to 2004 he directed the National Competence Center in Research on mobile information and communication systems. He is also a Vice-President for International Affairs at EPFL since October 2004. He has held visiting positions at ETHZ (1990) and Stanford (1998). He is a fellow of the IEEE, a member of SIAM, and was the Area Editor for Speech, Image, Video, and Signal Processing of the IEEE Transactions on Communications. He is also on the editorial boards of Annals of Telecommunications, Applied and Computational Harmonic Analysis and The Journal of Fourier Analysis and Application. He received the Best Paper Award of EURASIP in 1984 for his paper on multidimensional subband coding, the Research Prize of the Brown Bovery Corporation (Switzerland) in 1986 for his doctoral thesis, the IEEE Signal Processing Society's Senior Awards in 1991 and in 1996 (for papers with D. LeGall and K. Ramchandran, respectively). He won the Swiss National Latsis Prize in 1996, the SPIE Presidential award in 1999, and the IEEE Signal Processing Technical Achievement Award in 2001. He was a member of the Swiss Council on Science and Technology until Dec. 2003. He was a plenary speaker at various conferences (e.g. 1992 IEEE ICASSP) and is the co-author, with J. Kovacevic, of the book Wavelets and Subband Coding (Prentice-Hall, 1995). He has published about 85 journal papers on a variety of topics in signal/image processing and communications and holds 7 patents. His research interests include sampling, wavelets, multirate signal processing, computational complexity, signal processing for communications, digital video processing and joint source/channel coding.