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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8707811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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