Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia
This article aims to socialize the results of the development and implementation of a system based on IOT for aquifers, with its application in the estuary of the Rio Magdalena in Colombia. The SISME software supports the identification processes of different factors that can influence the appearanc...
- Autores:
-
Ariza Colpas, Paola Patricia
Ayala Mantilla, Cristian Eduardo
Piñeres Melo, Marlon Alberto
Villate-Daza, Diego Andrés
Morales Ortega, Roberto
Sanchez Moreno, Hernando
Butt Shariq, Aziz
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/8698
- Acceso en línea:
- https://hdl.handle.net/11323/8698
https://doi.org/10.1016/j.procs.2021.07.073
https://repositorio.cuc.edu.co/
- Palabra clave:
- Magdalena river
IOT in acuifers
Saline wedge
Monitoring system
- Rights
- openAccess
- License
- CC0 1.0 Universal
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|
dc.title.spa.fl_str_mv |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
title |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
spellingShingle |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia Magdalena river IOT in acuifers Saline wedge Monitoring system |
title_short |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
title_full |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
title_fullStr |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
title_full_unstemmed |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
title_sort |
Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia |
dc.creator.fl_str_mv |
Ariza Colpas, Paola Patricia Ayala Mantilla, Cristian Eduardo Piñeres Melo, Marlon Alberto Villate-Daza, Diego Andrés Morales Ortega, Roberto Sanchez Moreno, Hernando Butt Shariq, Aziz |
dc.contributor.author.spa.fl_str_mv |
Ariza Colpas, Paola Patricia Ayala Mantilla, Cristian Eduardo Piñeres Melo, Marlon Alberto Villate-Daza, Diego Andrés Morales Ortega, Roberto Sanchez Moreno, Hernando Butt Shariq, Aziz |
dc.subject.spa.fl_str_mv |
Magdalena river IOT in acuifers Saline wedge Monitoring system |
topic |
Magdalena river IOT in acuifers Saline wedge Monitoring system |
description |
This article aims to socialize the results of the development and implementation of a system based on IOT for aquifers, with its application in the estuary of the Rio Magdalena in Colombia. The SISME software supports the identification processes of different factors that can influence the appearance of the saline wedge in the navigable channel of the river. These aspects bring about the improvement of maritime safety and, in turn, allow us to know different aspects related to behavior through continuous sensing of the river. This article shows both the characterization of this river as well as studies related to it and the location of the sensors and description of the software developed. |
publishDate |
2021 |
dc.date.accessioned.none.fl_str_mv |
2021-09-15T16:21:14Z |
dc.date.available.none.fl_str_mv |
2021-09-15T16:21:14Z |
dc.date.issued.none.fl_str_mv |
2021 |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_6501 |
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acceptedVersion |
dc.identifier.issn.spa.fl_str_mv |
1877-0509 |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/8698 |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.procs.2021.07.073 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
identifier_str_mv |
1877-0509 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
url |
https://hdl.handle.net/11323/8698 https://doi.org/10.1016/j.procs.2021.07.073 https://repositorio.cuc.edu.co/ |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.references.spa.fl_str_mv |
[1] PROCIÉNAGA, 1994. Estudio de impacto ambiental. Proyecto: Reapertura de canales en el delta exterior derecho del río Magdalena. Inf. Proy. PROCIÉNAGA, Santa Marta, p. [2] Wiedemann, H. 1973. Reconnaissance of the Cienaga Grande de Santa Marta, Colombia: Physical Parameters and Geological History. Mitt. Inst. Colombo-Alemán Invest. Cient., 7: 85-119.. [3] Restrepo J, 2014. “Dinámica Sedimentaria en Deltas Micromareales – Estratificados de Alta Descarga: Delta del Rio Magdalena (Colombia – Mar Caribe)” Tesis Doctoral, Universidad del Norte –Barranquilla Atlantico. P 80-83. [4] Barandi, N. (2008). Implementación conjunta de sensores submarinos para mejorar. IEEE Xplorer. [5] Jacopo Aguzzi, A. M. (2011). The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring. sensors, 5850-5872. [6] Nima Bahrami, M. I. (2016). Study of Underwater Channel Estimation Based on. IEEE SENSORS JOURNAL, 1095-2016. [7] Kenneth K. K. Ku, R. B. (2008). A low-cost, three-dimensional, and real-time marine environment monitoring system, DatabuoyM with connection to the internet. OCEANS', 12-25. [8] Ariza-Colpas, P. P., Ayala-Mantilla, C. E., Shaheen, Q., Piñeres-Melo, M. A., Villate-Daza, D. A., Morales-Ortega, R. C., ... & Afzal, M. (2021). SISME, Estuarine Monitoring System Based on IOT and Machine Learning for the Detection of Salt Wedge in Aquifers: Case Study of the Magdalena River Estuary. Sensors, 21(7), 2374. |
dc.rights.spa.fl_str_mv |
CC0 1.0 Universal |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/publicdomain/zero/1.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
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CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
dc.publisher.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.source.spa.fl_str_mv |
Procedia Computer Science |
institution |
Corporación Universidad de la Costa |
dc.source.url.spa.fl_str_mv |
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Ariza Colpas, Paola PatriciaAyala Mantilla, Cristian EduardoPiñeres Melo, Marlon AlbertoVillate-Daza, Diego AndrésMorales Ortega, RobertoSanchez Moreno, HernandoButt Shariq, Aziz2021-09-15T16:21:14Z2021-09-15T16:21:14Z20211877-0509https://hdl.handle.net/11323/8698https://doi.org/10.1016/j.procs.2021.07.073Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This article aims to socialize the results of the development and implementation of a system based on IOT for aquifers, with its application in the estuary of the Rio Magdalena in Colombia. The SISME software supports the identification processes of different factors that can influence the appearance of the saline wedge in the navigable channel of the river. These aspects bring about the improvement of maritime safety and, in turn, allow us to know different aspects related to behavior through continuous sensing of the river. This article shows both the characterization of this river as well as studies related to it and the location of the sensors and description of the software developed.Ariza Colpas, Paola Patricia-will be generated-orcid-0000-0003-4503-5461-600Ayala Mantilla, Cristian Eduardo-will be generated-orcid-0000-0002-1475-7827-600Piñeres Melo, Marlon Alberto-will be generated-orcid-0000-0002-1858-2083-600Villate-Daza, Diego AndrésMorales Ortega, Roberto-will be generated-orcid-0000-0002-8219-9943-600Sanchez Moreno, Hernando-will be generated-orcid-0000-0003-1435-1760-600Butt Shariq, Azizapplication/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Procedia Computer Sciencehttps://www.sciencedirect.com/science/article/pii/S1877050921014769#!Magdalena riverIOT in acuifersSaline wedgeMonitoring systemReal time monitoring system for the detection of saline wedge in the Magdalena River – ColombiaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] PROCIÉNAGA, 1994. Estudio de impacto ambiental. Proyecto: Reapertura de canales en el delta exterior derecho del río Magdalena. Inf. Proy. PROCIÉNAGA, Santa Marta, p.[2] Wiedemann, H. 1973. Reconnaissance of the Cienaga Grande de Santa Marta, Colombia: Physical Parameters and Geological History. Mitt. Inst. Colombo-Alemán Invest. Cient., 7: 85-119..[3] Restrepo J, 2014. “Dinámica Sedimentaria en Deltas Micromareales – Estratificados de Alta Descarga: Delta del Rio Magdalena (Colombia – Mar Caribe)” Tesis Doctoral, Universidad del Norte –Barranquilla Atlantico. P 80-83.[4] Barandi, N. (2008). Implementación conjunta de sensores submarinos para mejorar. IEEE Xplorer.[5] Jacopo Aguzzi, A. M. (2011). The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring. sensors, 5850-5872.[6] Nima Bahrami, M. I. (2016). Study of Underwater Channel Estimation Based on. IEEE SENSORS JOURNAL, 1095-2016.[7] Kenneth K. K. Ku, R. B. (2008). A low-cost, three-dimensional, and real-time marine environment monitoring system, DatabuoyM with connection to the internet. OCEANS', 12-25.[8] Ariza-Colpas, P. P., Ayala-Mantilla, C. E., Shaheen, Q., Piñeres-Melo, M. A., Villate-Daza, D. A., Morales-Ortega, R. C., ... & Afzal, M. (2021). SISME, Estuarine Monitoring System Based on IOT and Machine Learning for the Detection of Salt Wedge in Aquifers: Case Study of the Magdalena River Estuary. 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