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. 2025 Apr 30;25(9):2824.
doi: 10.3390/s25092824.

A Low-Cost pH Sensor for Real-Time Monitoring of Aquaculture Systems in a Multi-Layer Wireless Sensor Network

Binta Mohammed Adib Zeta  1 , Sifat U Alam  1 , Gazi M A Ehsan Ur Rahman  1 , Khawza Iftekhar Uddin Ahmed  1   2
Affiliations

A Low-Cost pH Sensor for Real-Time Monitoring of Aquaculture Systems in a Multi-Layer Wireless Sensor Network

Binta Mohammed Adib Zeta et al. Sensors (Basel). .

Abstract

For aquaculture systems, pH is the prime quality indicator and is highly related to other water quality indicators like ammonia and ammonium ions. The available pH sensors using chemical references are not suitable for continuous in situ monitoring of aquaculture systems due to their frequent calibration requirement and high cost. This research develops a pH sensor with temperature compensation implementing a machine learning (ML) algorithm. Unlike traditional methods, this sensor utilizes electronic calibration, eliminating the need for chemical calibration and ongoing maintenance efforts. The application of this low-cost sensor is particularly well suited for in situ aquaculture scenarios, where multiple local sensor nodes operate under the control of a master node. The test results of the developed sensor show an improved sensitivity from 0.288 µA/pH to 0.316 µA/pH compared to the available pH sensors. Additionally, the response time has been improved from 1 s to 125 ms, showcasing the suitability of this pH sensor for real-time water quality monitoring of aquaculture applications.

Keywords: aquaculture; electrode; pH sensor; temperature compensation.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Multiple sensors in a Biofloc tank at different depth and position communicating with a local control node.
Figure 2
Figure 2
System architecture with multi depth sensor nodes and control node, along with WSN-GW-IoT-User application.
Figure 3
Figure 3
Classification of pH sensors based on three different perspectives.
Figure 4
Figure 4
Features of proposed Solutions.
Figure 5
Figure 5
Behavior of the probe at different lengths. (a) Current response of pH sensor when probe length is 6 mm. (b) Relation between current and pH when probe length is 9.5 mm. (c) Current response of the sensor when probe length is 8 mm. (d) Current and pH relation with 10 mm probe length.
Figure 6
Figure 6
Pattern and length variants of sensor electrodes. Sensor probe A has 8 mm round shape gold plating; B has 9.5 mm and C has 10 mm gold plating.
Figure 7
Figure 7
Working principle of the sensor node.
Figure 8
Figure 8
The lab setup of the sensor. (a) Hardware block diagram of the pH sensor with control circuit. (b) Schematic diagram of the sensor.
Figure 9
Figure 9
Data collection and processing block diagram.
Figure 10
Figure 10
System Architecture of proposed solution where multiple sensor nodes are placed in different aquaculture systems. Control node collects sensor data and store the data to an IoT platform through a gateway.
Figure 11
Figure 11
Relationship between current and pH. (a) Current response of the pH sensor at different pH values. (b) Current and pH relation with high linearity.
Figure 12
Figure 12
Temperature compensation of the pH sensor. (a) Different pH values at different temperature without temperature compensation (b) Measured pH with respect to temperature using our temperature compensated pH sensor and a commercial pH meter.
Figure 13
Figure 13
Response time of the sensor. (a) Response time of the pH sensor when pH is 4 (b) Dynamic response time with alternation of pH.
Figure 14
Figure 14
Sensitivity of the sensor for different pH values at 25 °C.
Figure 15
Figure 15
Stability of the sensor; Measured median and standard deviation values of pH 6,7 and 8 over two days.
See this image and copyright information in PMC

References

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