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. 2021 Dec 7;21(24):8179.
doi: 10.3390/s21248179.

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

Jen-Yung Lin  1 , Huan-Liang Tsai  1 , Wei-Hong Lyu  1
Affiliations

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

Jen-Yung Lin et al. Sensors (Basel). .

Abstract

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.

Keywords: ThingSpeak IoT; ThingView APP; freshwater aquaculture; wireless multi-sensor system.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Global fish production of capture fisheries and aquaculture.
Figure 2
Figure 2
System schematic of wireless multi-sensor water quality monitoring system.
Figure 3
Figure 3
Schematics of sensors: (a) DS18B20 temperature sensor; (b) pH sensor; (c) DO sensor; and (d) EC sensor.
Figure 4
Figure 4
Snapshot of ThingSpeak IoT for water quality monitoring system.
Figure 5
Figure 5
Snapshot of ThingView APP for water quality monitoring system.
Figure 6
Figure 6
Flowchart of wireless multi-sensor module.
Figure 7
Figure 7
The 24 h measurement results of pre-calibration process: (a) DS18B20 temperature sensor vs. HEL-711 RTD; (b) pH sensor vs. pH 4.4 buffer solution; (c) pH sensor vs. pH 6.86 buffer solution; (d) pH sensor vs. pH 9.0 buffer solution; (e) DO sensor vs. FOPTOD ODO; (f) EC sensor vs. EC 1413 μS/cm solution; (g) EC sensor vs. EC 12.88 mS/cm solution; and (h) salinity estimation vs. Vernier salinity sensor.
Figure 7
Figure 7
The 24 h measurement results of pre-calibration process: (a) DS18B20 temperature sensor vs. HEL-711 RTD; (b) pH sensor vs. pH 4.4 buffer solution; (c) pH sensor vs. pH 6.86 buffer solution; (d) pH sensor vs. pH 9.0 buffer solution; (e) DO sensor vs. FOPTOD ODO; (f) EC sensor vs. EC 1413 μS/cm solution; (g) EC sensor vs. EC 12.88 mS/cm solution; and (h) salinity estimation vs. Vernier salinity sensor.
Figure 8
Figure 8
The 10-day in situ measurement results: (a) water temperature; (b) pH level; (c) DO level; (d) EC level; and (e) salinity level.
Figure 9
Figure 9
The 24 h measurement results of post-calibration process: (a) temperature; (b) pH level; (c) DO level; (d) EC level; and (e) salinity level.
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