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An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture

Water temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and salinity levels are the critical cultivation factors for freshwater aquaculture. This paper proposes a novel wireless multi-sensor system by integrating the temperature, pH, DO, and EC sensors with an ESP 32 Wi-Fi module...

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Autores principales: Lin, Jen-Yung, Tsai, Huan-Liang, Lyu, Wei-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8707811/
https://www.ncbi.nlm.nih.gov/pubmed/34960272
http://dx.doi.org/10.3390/s21248179
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author Lin, Jen-Yung
Tsai, Huan-Liang
Lyu, Wei-Hong
author_facet Lin, Jen-Yung
Tsai, Huan-Liang
Lyu, Wei-Hong
author_sort Lin, Jen-Yung
collection PubMed
description Water temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and salinity levels are the critical cultivation factors for freshwater aquaculture. This paper proposes a novel wireless multi-sensor system by integrating the temperature, pH, DO, and EC sensors with an ESP 32 Wi-Fi module for monitoring the water quality of freshwater aquaculture, which acquires the sensing data and salinity information directly derived from the EC level. The information of water temperature, pH, DO, EC, and salinity levels was displayed in the ThingSpeak IoT platform and was visualized in a user-friendly manner by ThingView APP. Firstly, these sensors were integrated with an ESP32 Wi-Fi platform. The observations of sensors and the estimated salinity from the EC level were then transmitted by a Wi-Fi network to an on-site Wi-Fi access point (AP). The acquired information was further transmitted to the ThingSpeak IoT and displayed in the form of a web-based monitoring system which can be directly visualized by online browsing or the ThingView APP. Through the complete processes of pre-calibration, in situ measurement, and post-calibration, the results illustrate that the proposed wireless multi-sensor IoT system has sufficient accuracy, reliable confidence, and a good tolerance for monitoring the water quality of freshwater aquaculture.
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spelling pubmed-87078112021-12-25 An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture Lin, Jen-Yung Tsai, Huan-Liang Lyu, Wei-Hong Sensors (Basel) Article Water temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and salinity levels are the critical cultivation factors for freshwater aquaculture. This paper proposes a novel wireless multi-sensor system by integrating the temperature, pH, DO, and EC sensors with an ESP 32 Wi-Fi module for monitoring the water quality of freshwater aquaculture, which acquires the sensing data and salinity information directly derived from the EC level. The information of water temperature, pH, DO, EC, and salinity levels was displayed in the ThingSpeak IoT platform and was visualized in a user-friendly manner by ThingView APP. Firstly, these sensors were integrated with an ESP32 Wi-Fi platform. The observations of sensors and the estimated salinity from the EC level were then transmitted by a Wi-Fi network to an on-site Wi-Fi access point (AP). The acquired information was further transmitted to the ThingSpeak IoT and displayed in the form of a web-based monitoring system which can be directly visualized by online browsing or the ThingView APP. Through the complete processes of pre-calibration, in situ measurement, and post-calibration, the results illustrate that the proposed wireless multi-sensor IoT system has sufficient accuracy, reliable confidence, and a good tolerance for monitoring the water quality of freshwater aquaculture. MDPI 2021-12-07 /pmc/articles/PMC8707811/ /pubmed/34960272 http://dx.doi.org/10.3390/s21248179 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lin, Jen-Yung
Tsai, Huan-Liang
Lyu, Wei-Hong
An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title_full An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title_fullStr An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title_full_unstemmed An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title_short An Integrated Wireless Multi-Sensor System for Monitoring the Water Quality of Aquaculture
title_sort integrated wireless multi-sensor system for monitoring the water quality of aquaculture
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8707811/
https://www.ncbi.nlm.nih.gov/pubmed/34960272
http://dx.doi.org/10.3390/s21248179
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