Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity

Hydrologists claim high-quality experimental data are required to improve the understanding of hydrological processes. Though accurate devices for measuring hydrological processes are available, the on-site deployment and operation of effective monitoring networks face many relevant issues caused by the peculiar characteristics of hydrological systems. In this manuscript, we present a self-developed system for monitoring events-based hydrological processes comprising a dense network with both soil moisture and water level gauges connected by NB-IoT technology integrated into a cloud system for near real-time gathering of information. We designed, built and calibrated the sensors and integrated them into a cloud system. We deployed them in two monitoring networks and gathered the data from several experimental runs (battery lifecycles). Results showed the suitability of the sensors and the network to properly monitor the processes solving the initial relevant issues mainly derived from connectivity issues and battery duration.

Authors

Institutions

Publication Details

Journal
Environmental Modelling & Software
Published
2024-08-11
DOI
https://doi.org/10.1016/j.envsoft.2024.106186
Citations
6
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
1.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity

Jorge Sastre, Jorge Trincado, Ernesto Sanz, José Manuel Molina et al.
6 citations
Environmental Modelling & Software
Water Quality Monitoring Technologies
1.21
article

Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity

Jorge Sastre, Jorge Trincado, Ernesto Sanz, José Manuel Molina, Sergio Zubelzu, Miguel Á. Patricio, Antonio Berlanga, Jorge Payno, Omer Morante, Andrés F. Almeida-Ñaulay
article en
6 citations

Abstract

Hydrologists claim high-quality experimental data are required to improve the understanding of hydrological processes. Though accurate devices for measuring hydrological processes are available, the on-site deployment and operation of effective monitoring networks face many relevant issues caused by the peculiar characteristics of hydrological systems. In this manuscript, we present a self-developed system for monitoring events-based hydrological processes comprising a dense network with both soil moisture and water level gauges connected by NB-IoT technology integrated into a cloud system for near real-time gathering of information. We designed, built and calibrated the sensors and integrated them into a cloud system. We deployed them in two monitoring networks and gathered the data from several experimental runs (battery lifecycles). Results showed the suitability of the sensors and the network to properly monitor the processes solving the initial relevant issues mainly derived from connectivity issues and battery duration.

Environmental Modelling & SoftwareVol. 182
Universidad Carlos III de Madrid (ES), Universidad Politécnica de Madrid (ES)
Ministerio de Ciencia, Innovación y Universidades
Openalex Percentile: Top 23%
Water Quality Monitoring Technologies
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.