ASPIRE: Collaborative Signal Processing for Efficient Wireless Sensor Networks
Dates: 09/2006 – 08/2010
Funded by: European Commission, 6th Framework Programme, Marie Curie Transfer of Knowledge (ToK-DEV) Grant
Project Coordinator: P. Tsakalides
Collaborators: Baltasar Beferull-Lozano (University of Valencia, Spain) and C. Kyriakakis (University of Southern California, USA)
Funding: € 1,256,423
Summary: Wireless sensor networks (WSN) have been an emerging technology whose goal is to monitor the physical world by means of a densely distributed network of wireless sensor nodes. It will soon become feasible to deploy massive amounts of inexpensive devices to observe large ground surfaces, underwater regions, and areas in the atmosphere. These devices, integrated with miniature power supply, multiple modality sensors, on-board processors, and radio communication modules, will be capable of forming a large-scale ad hoc WSN. If judiciously and successfully deployed, they will be able to provide, to the benefit of society and several scientific communities (e.g. environmental science), unprecedented opportunities for instrumenting and controlling the environment, our cities, both our microcosm and macrocosm.
Realising the potential of large, distributed sensor networks requires major advances in the theory, fundamental understanding and practice of distributed data processing, self-organised communications, and information fusion in highly uncertain scenarios using sensing/communications nodes that are severely constrained in power, computation, and communication capabilities.
The ASPIRE project is pushing the boundaries of wireless sensor networks. By approaching traditional, entrenched problems from innovative new angles, the project is breaking through the ‘wireless sensor node’ glass ceiling. During the period 2006-2010, the ASPIRE Group has been active and productive in original research in 5 major axes, namely: (i) Distributed signal classification for wireless sensor networks; (ii) Compressive sensing (CS) and its applications; (iii) Multichannel audio coding and transmission; (iv) Non-Gaussian modeling and multiscale Bayesian processing for various signal modalities; and (v) Wireless network traffic modeling and localization in WSNs.
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