An IoT-based scalable river level monitoring platform

Juan Acosta, Diego Mendez, Daniel Moreno, German Montanez, Luis Trujillo, Mauricio Escobar, Ignacio Gonzalez

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Due to extreme natural conditions, there is a clear necessity of cost-effective and scalable solutions to continuously monitor the environmental conditions in order to take precautionary actions. In this paper, we present the design and implementation of an IoT-based solution for river level monitoring. The implemented system integrates 31 stations with communication capabilities to monitor the status of the Negro and Nare rivers. An embedded system has been designed and implemented from scratch into a single PCB, integrating ultrasonic sensors and power management. In order to consolidate and visualise the data, a cloud platform has been implemented, which is also in charge of generating alerts to local authorities and the population in general. The stations have an autonomy of 22 days in case of complete solar panel damage. The experimental results show that the river dynamics are perfectly captured in real-time allowing the authorities to timely warn the population.

Original languageEnglish
Pages (from-to)263-272
Number of pages10
JournalInternational Journal of Sensor Networks
Volume38
Issue number4
DOIs
StatePublished - 2022

Keywords

  • early warning system
  • embedded system
  • floods
  • river level

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