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Title Dynamic, Rule-based Quality Control Framework for Real-time Sensor Data
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The volume of monitoring data that can be acquired and managed by Long Term Ecological Research sites and environmental observatories has increased exponentially over time, thanks to advances in sensor technology and computing power combined with steady decreases in data storage costs. New directions in environmental monitoring, such as sensor networks and instrumented platforms with real-time data telemetry, are raising the bar even higher. Quality control is often a major challenge with real-time data, though, due to poor scalability of traditional software tools, approaches and analysis methods. Software developed at the Georgia Coastal Ecosystems Long Term Ecological Research Site (GCE Data Toolbox for MATLAB) has proven very effective for quality control of both real-time and legacy data, as well as interactive analysis during post processing and synthesis. This paper describes the design and operation of the dynamic, rule-based quality control framework provided by this software, and presents quantitative performance data that demonstrate these tools can efficiently perform quality analysis on million-record data sets using commodity computer hardware.

Contributor Wade M. Sheldon

Sheldon, W.M. Jr. 2008. Dynamic, Rule-based Quality Control Framework for Real-time Sensor Data. Pages 145-150 in: Gries, C. and Jones, M.B. (editors). Proceedings of the Environmental Information Management Conference 2008 (EIM 2008): Sensor Networks. Albuquerque, New Mexico.

Key Words data, information management, LTER-IMC, MATLAB, quality control, sensor, software
File Date 2008
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This material is based upon work supported by the National Science Foundation under grants OCE-9982133, OCE-0620959, OCE-1237140 and OCE-1832178. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.