Imagine a world in which we live where smart roads would be able to tell us when they need repair and which is the best direction to get to the Giants game, smart factories would stock up just enough inventory, ...  The rapid advances in micro-electro-mechanical systems (MEMS) and lower-power wireless networking have enabled a new generation of tiny, cheap, networked sensors that can be "sprayed" on roads, across machines, and on walls. However, these massively distributed sensor networks must overcome a set of technological hurdles before they become widely deployable.  Keeping up with the constant onslaught of sensory data from say 100,000 sensors is akin to drinking from a fire hose.

The PARC Smart Matter Diagnostics and Collaborative Sensemaking Project studies the fundamental problems of distilling high-level, human-interpretable knowledge from distributed heterogeneous sensor signals in a rapid and scalable manner.  We are developing powerful algorithms and software systems to enable a wide range of applications, from sensor-rich health monitoring of electro-mechanical equipment to human-aware environments that leverage sensors to support synergistic interactions with the physical world.

M. Chu, H. Haussecker, F. Zhao, "Scalable information-driven sensor querying and routing for ad hoc heterogeneous sensor networks." Int'l J. High Performance Computing Applications, to appear, 2002. Also, Xerox Palo Alto Research Center Technical Report P2001-10113, May 2001. Paper (pdf).

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