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Real-time Monitoring and Control of a Biofloc System Based on the Internet of Things

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By Milthon Lujan

Graphical Summary of the Study. Source: Al Mamun et al., (2024); Smart Agricultural Technology, 9, 100598.
Graphical Summary of the Study. Source: Al Mamun et al., (2024); Smart Agricultural Technology, 9, 100598.

Biofloc technology has gained significant traction in the aquaculture sector of Bangladesh, offering a sustainable and efficient approach to fish farming. However, maintaining optimal water parameters is essential to maximize yields and ensure the health of fish populations.

A study published by researchers from the Department of Farm Power and Machinery at Bangladesh Agricultural University in the scientific journal Smart Agricultural Technology presents an innovative Internet of Things (IoT)-enabled monitoring system designed to automate the regulation of these parameters, thereby improving the productivity and sustainability of biofloc aquaculture.

The Importance of Water Quality in Biofloc Aquaculture

Biofloc systems, characterized by low water exchange and enhanced water quality, have gained great popularity in aquaculture. However, maintaining optimal water conditions is essential for the health and productivity of aquatic organisms. Key water parameters, including temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), turbidity, and ammonia, directly influence the growth, survival, and reproductive success of fish.

Application of IoT in Aquaculture

Traditional methods of monitoring water quality often involve manual testing, which can be time-consuming, labor-intensive, and prone to inaccuracies. The fluctuating nature of water parameters makes it difficult to maintain constant monitoring and control through manual techniques.

The Internet of Things (IoT) has revolutionized the monitoring and control of water quality parameters in aquaculture. IoT-enabled sensors can continuously monitor temperature, pH, turbidity, total dissolved solids (TDS), dissolved oxygen (DO), and water level in real time. These sensors can transmit data to a microcontroller, which processes the information and sends alerts to mobile devices and computers via the Blynk app if any of the parameters deviate from expected values.

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Key Components of an IoT-Based Water Quality Monitoring System

  • Sensors: Various sensors can be deployed to measure temperature, pH, dissolved oxygen, turbidity, total dissolved solids (TDS), ammonia, and other relevant parameters.
  • Wireless communication: Technologies such as Wi-Fi, Bluetooth, or cellular networks enable the transmission of data from sensors to a central control unit.
  • Data analysis: Advanced algorithms and machine learning techniques can analyze sensor data to identify trends, anomalies, and potential issues.
  • Automation: Control systems can be integrated to automatically adjust parameters such as aeration rates or feed inputs based on real-time data.

System Design and Implementation

The proposed system uses a network of sensors to collect real-time data on temperature, total dissolved solids (TDS), pH, turbidity, dissolved oxygen (DO), and water level. These parameters are critical for maintaining a healthy biofloc environment. An IoT platform, powered by the ESP32 microcontroller, is used to process and analyze the sensor data, allowing for remote monitoring and control.

The study focused on Nile tilapia (Oreochromis niloticus) as the target species. The system was calibrated to maintain optimal conditions: temperature around 27 ± 1°C, DO around 6 ± 0.5 mg/l, TDS around 500 ppm, and pH near 7.7 ± 0.5. Deviations from these set points triggered automatic responses, such as activating or deactivating water heaters, pumps, and air pumps.

Study Results

The IoT-enabled monitoring system proved effective in maintaining ideal biofloc conditions throughout the experiment. By continuously tracking and adjusting parameters, the system helped optimize fish growth, reduce mortality rates, and improve overall aquaculture efficiency.

Key findings of the study include:

  • Real-time monitoring: The system provided accurate and timely data on biofloc parameters, enabling proactive interventions when necessary.
  • Automated control: Automated response mechanisms ensured that water quality remained within optimal ranges, minimizing human intervention and reducing the risk of errors.
  • Productivity improvement: By maintaining a stable and healthy environment, the IoT system contributed to enhanced fish growth and reduced mortality rates, resulting in increased production.
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Conclusion

The IoT-enabled monitoring and control system for biofloc systems represents a significant advancement in aquaculture technology. By providing real-time data and enabling automated control, this system offers a sustainable and efficient solution for managing biofloc systems.

As the aquaculture industry continues to grow, the adoption of such innovative technologies will be essential to ensuring long-term sustainability and profitability.

Contact
Muhammad Ashik-E-Rabbani
Department of Farm Power and Machinery, Bangladesh Agricultural University
Mymensingh, Bangladesh
Email: ashik@bau.edu.bd

Reference (open access)
Al Mamun, M. R., Ashik-E-Rabbani, M., Haque, M. M., & Upoma, S. M. (2024). IoT-based real-time biofloc monitoring and controlling system. Smart Agricultural Technology, 9, 100598. https://doi.org/10.1016/j.atech.2024.100598