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

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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Bibliographic Details
Main Authors: Paola Patricia Ariza-Colpas, Cristian Eduardo Ayala-Mantilla, Qaisar Shaheen, Marlon Alberto Piñeres-Melo, Diego Andrés Villate-Daza, Roberto Cesar Morales-Ortega, Emiro De-la-Hoz-Franco, Hernando Sanchez-Moreno, Butt Shariq Aziz, Mehtab Afzal
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
IOT systems
machine learning
salt wedge
aquifers
Magdalena river estuary
Online Access:https://www.mdpi.com/1424-8220/21/7/2374

Internet

https://www.mdpi.com/1424-8220/21/7/2374

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