An environmental sensor network to determine drinking water quality and security

Finding patterns in large, real, spatio/temporal data continues to attract high interest (e.g., sales of products over space and time, patterns in mobile phone users; sensor networks collecting operational data from automobiles, or even from humans with wearable computers). In this paper, we describe an interdisciplinary research effort to couple knowledge discovery in large environmental databases with biological and chemical sensor networks, in order to revolutionize drinking water quality and security decision making. We describe a distribution and operation protocol for the placement and utilization of in situ environmental sensors by combining (1) new algorithms for spatialtemporal data mining, (2) new methods to model water quality and security dynamics, and (3) a sophisticated decision-analysis framework. The project was recently funded by NSF and represents application of these research areas to the critical current issue of ensuring safe and secure drinking water to the population of the United States.

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