Near optimal sensor selection in the COlumbia RIvEr (CORIE) observation network for data assimilation using genetic algorithms

Thanh Dang, Sergey Frolov, Nirupama Bulusu, Wu Chi Feng, António Baptista

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Scopus citations

    Abstract

    CORIE is a pilot environmental observation and forecasting system (EOFS) for the Columbia River. The goal of CORIE is to characterize and predict complex circulation and mixing processes in a system encompassing the lower river, the estuary, and the near-ocean using a multi-scale data assimilation model. The challenge for scientists is to maintain the accuracy of their modeling system while minimizing resource usage. In this paper, we first propose a metric for characterizing the error in the CORIE data assimilation model and study the impact of the number of sensors on the error reduction. Second, we propose a genetic algorithm to compute the optimal configuration of sensors that reduces the number of sensors to the minimum required while maintaining a similar level of error in the data assimilation model. We verify the results of our algorithm with 30 runs of the data assimilation model. Each run uses data collected and estimated over a two-day period. We can reduce the sensing resource usage by 26.5% while achieving comparable error in data assimilation. As a result, we can potentially save 40 thousand dollars in initial expenses and 10 thousand dollars in maintenance expense per year. This algorithm can be used to guide operation of the existing observation network, as well as to guide deployment of future sensor stations. The novelty of our approach is that our problem formulation of network configuration is influenced by the data assimilation framework which is more meaningful to domain scientists, rather than using abstract sensing models.

    Original languageEnglish (US)
    Title of host publicationDistributed Computing in Sensor Systems - Third IEEE International Conference, DCOSS 2007, Proceedings
    PublisherSpringer-Verlag
    Pages253-266
    Number of pages14
    ISBN (Print)3540730893, 9783540730897
    DOIs
    StatePublished - 2007
    Event3rd IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2007 - Santa Fe, NM, United States
    Duration: Jun 18 2007Jun 20 2007

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4549 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other3rd IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2007
    Country/TerritoryUnited States
    CitySanta Fe, NM
    Period6/18/076/20/07

    Keywords

    • Coastal monitoring
    • Data assimilation
    • Genetic algorithm
    • Network configuration
    • Sensor selection

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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