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

This article contains methods, results, and analysis agreed for the development of an application based on the internet of things and making use of machine learning techniques that serves as a support for the identification of the saline wedge in the Magdalena River estuary, Colombia. As a result of...

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Detalles Bibliográficos
Autores principales: Ariza-Colpas, Paola Patricia, Ayala-Mantilla, Cristian Eduardo, Shaheen, Qaisar, Piñeres-Melo, Marlon Alberto, Villate-Daza, Diego Andrés, Morales-Ortega, Roberto Cesar, De-la-Hoz-Franco, Emiro, Sanchez-Moreno, Hernando, Aziz, Butt Shariq, Afzal, Mehtab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036609/
https://www.ncbi.nlm.nih.gov/pubmed/33805544
http://dx.doi.org/10.3390/s21072374

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036609/
https://www.ncbi.nlm.nih.gov/pubmed/33805544
http://dx.doi.org/10.3390/s21072374

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