Dynamically identifying and tracking contaminants in water bodies

Craig C. Douglas; Martin J. Cole; Paul Dostert; Yalchin Efendiev; Richard E. Ewing; Gundolf Haase; Jay Hatcher; Mohamed Iskandarani; Chris R. Johnson; Robert A. Lodder

doi:10.1007/978-3-540-72584-8_132

Dynamically identifying and tracking contaminants in water bodies

Craig C. Douglas, Martin J. Cole, Paul Dostert, Yalchin Efendiev, Richard E. Ewing, Gundolf Haase, Jay Hatcher, Mohamed Iskandarani, Chris R. Johnson, Robert A. Lodder

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

We present an overview of an ongoing project to build a DDDAS for identifying and tracking chemicals in water. The project involves a new class of intelligent sensor, building a library to optically identify molecules, communication techniques for moving objects, and a problem solving environment. We are developing an innovative environment so that we can create a symbiotic relationship between computational models for contaminant identification and tracking in water bodies and a new instrument, the Solid-State Spectral Imager (SSSI), to gather hydrological and geological data and to perform chemical analyses. The SSSI is both small and light and can scan ranges of up to about 10 meters. It can easily be used with remote sensing applications.

Original language	English
Title of host publication	Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I
Pages	1002-1009
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-540-72584-8_132
State	Published - 2007
Event	7th International Conference on Computational Science, ICCS 2007 - Beijing, China Duration: May 27 2007 → May 30 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4487 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	7th International Conference on Computational Science, ICCS 2007
Country/Territory	China
City	Beijing
Period	5/27/07 → 5/30/07

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-72584-8_132

Cite this

Douglas, C. C., Cole, M. J., Dostert, P., Efendiev, Y., Ewing, R. E., Haase, G., Hatcher, J., Iskandarani, M., Johnson, C. R., & Lodder, R. A. (2007). Dynamically identifying and tracking contaminants in water bodies. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I (pp. 1002-1009). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4487 LNCS). https://doi.org/10.1007/978-3-540-72584-8_132

Douglas, Craig C. ; Cole, Martin J. ; Dostert, Paul et al. / Dynamically identifying and tracking contaminants in water bodies. Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. 2007. pp. 1002-1009 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We present an overview of an ongoing project to build a DDDAS for identifying and tracking chemicals in water. The project involves a new class of intelligent sensor, building a library to optically identify molecules, communication techniques for moving objects, and a problem solving environment. We are developing an innovative environment so that we can create a symbiotic relationship between computational models for contaminant identification and tracking in water bodies and a new instrument, the Solid-State Spectral Imager (SSSI), to gather hydrological and geological data and to perform chemical analyses. The SSSI is both small and light and can scan ranges of up to about 10 meters. It can easily be used with remote sensing applications.",

author = "Douglas, {Craig C.} and Cole, {Martin J.} and Paul Dostert and Yalchin Efendiev and Ewing, {Richard E.} and Gundolf Haase and Jay Hatcher and Mohamed Iskandarani and Johnson, {Chris R.} and Lodder, {Robert A.}",

year = "2007",

doi = "10.1007/978-3-540-72584-8_132",

language = "English",

isbn = "9783540725831",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "1002--1009",

booktitle = "Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I",

note = "7th International Conference on Computational Science, ICCS 2007 ; Conference date: 27-05-2007 Through 30-05-2007",

}

Douglas, CC, Cole, MJ, Dostert, P, Efendiev, Y, Ewing, RE, Haase, G, Hatcher, J, Iskandarani, M, Johnson, CR & Lodder, RA 2007, Dynamically identifying and tracking contaminants in water bodies. in Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4487 LNCS, pp. 1002-1009, 7th International Conference on Computational Science, ICCS 2007, Beijing, China, 5/27/07. https://doi.org/10.1007/978-3-540-72584-8_132

Dynamically identifying and tracking contaminants in water bodies. / Douglas, Craig C.; Cole, Martin J.; Dostert, Paul et al.
Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. 2007. p. 1002-1009 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4487 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Cole, Martin J.

AU - Dostert, Paul

AU - Efendiev, Yalchin

AU - Ewing, Richard E.

AU - Haase, Gundolf

AU - Hatcher, Jay

AU - Iskandarani, Mohamed

AU - Johnson, Chris R.

AU - Lodder, Robert A.

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AB - We present an overview of an ongoing project to build a DDDAS for identifying and tracking chemicals in water. The project involves a new class of intelligent sensor, building a library to optically identify molecules, communication techniques for moving objects, and a problem solving environment. We are developing an innovative environment so that we can create a symbiotic relationship between computational models for contaminant identification and tracking in water bodies and a new instrument, the Solid-State Spectral Imager (SSSI), to gather hydrological and geological data and to perform chemical analyses. The SSSI is both small and light and can scan ranges of up to about 10 meters. It can easily be used with remote sensing applications.

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Douglas CC, Cole MJ, Dostert P, Efendiev Y, Ewing RE, Haase G et al. Dynamically identifying and tracking contaminants in water bodies. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. 2007. p. 1002-1009. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-72584-8_132

Dynamically identifying and tracking contaminants in water bodies

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