Multiparametric System for Measuring Physicochemical Variables Associated to Water Quality Based on the Arduino Platform

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Traditionally, the estimation of water quality is realized through laboratory analysis which is time-consuming and requires specialized installations, equipment, and personnel. Nowadays, it is possible to make real-time water monitoring through electrochemical sensors, microcontrollers, and central processing units to detect water pollutants. This work proposes a system based on the Arduino platform for monitoring parameters associated with water quality, such as oxidation-reduction potential, pH, total dissolved solids, turbidity, temperature, electrical conductivity, and dissolved oxygen. A critical criterion for the sensor selection was its cost and availability, resulting in sensors from different companies. They were integrated without much complexity, thanks to the selected platform. In addition, a proposal is made for a signal conditioning circuit for the oxidation-reduction potential electrode. A stage of filtering is added to the pH and turbidity commercial circuits to improve their performance. Remote access to the data is done through a mini-PC with WIFI connectivity and a MySQL database. All the sensors were calibrated with reference solutions or against other commercial meters. Through the proposed system, time series having a sampling period of 20 s of all parameters were recorded for more than a week-long exhibiting circadian patterns for the same water sample. Pearson correlation for the parameters was carried on. The results show that the system successfully monitored the seven physicochemical variables through low-cost sensors. It also has remote access capabilities.

Original languageEnglish
Pages (from-to)69700-69713
Number of pages14
JournalIEEE Access
Volume10
DOIs
StatePublished - 2022

Keywords

  • Arduino
  • MySQL
  • PC
  • dissolved oxygen
  • electrical conductivity
  • oxidation-reduction potential
  • pH
  • temperature
  • time-series
  • total dissolved solids
  • turbidity
  • water quality monitoring

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