Data-Driven Water Monitoring System with Descriptive Analytics for Aquaculture Prawn Farms

Authors

  • Augustin C. Borbon College of Arts and Sciences, Iloilo Science and Technology University, La Paz, Iloilo City, Philippines
  • Ramil G. Lumauag Iloilo Science and Technology University – Dumangas Campus, Dumangas, Iloilo, Philippines

DOI:

https://doi.org/10.69478/JITC2024v6n3a08

Keywords:

Aquaculture, Water monitoring system device, Microprocessor, Sensors

Abstract

This study aimed to develop a data-driven water monitoring system with descriptive analytics for aquaculture prawn farms. This system was designed to automate the monitoring of the water quality of the prawn farm so as to minimize labor and time spent for manually testing the water. Utilizing a rapid prototyping methodology, which is a rapid or quick creation of a prototype or a physical model of a device used in the development of a project, the said monitoring system was evaluated through a comparative analysis between the data gathered manually and the data collected by the monitoring system. To ensure reliability and validity of this monitoring system, it was used various times over several consecutive days. Also, a t-test was used to determine the significant differences between manual and system readings. Findings of the study showed that the designed water monitoring system provided accurate results, and the objectives of the study were met, particularly in terms of integrating a Raspberry Pi 3 microprocessor to automate the system in monitoring the water quality. It was also found out that the use of different sensors to test the water condition in terms of its temperature, pH level, salinity, dissolved oxygen, and turbidity was accurate. Furthermore, the system also met its objective of developing an Android mobile application to monitor the status remotely. With this, it is recommended for prawn farmers to utilize the system (with internet connectivity) for their efficient water quality management and to improve their remote monitoring capabilities.

References

Alune, “How to Manage Water Effluent from Shrimp Farms”, The Fish Site, June 2021, https://thefishsite.com/articles/how-to-manage-water-effluent-from-shrimp-farms.

J. C. V. Vergel, “Current Trends in the Philippines’ Shrimp Aquaculture Industry: A Booming Blue Economy in the Pacific”, Oceanography and Fisheries Open Access Journal, vol. 5, no. 4, December 2017, pp. 1-5, https://doi.org/10.19080/OFOAJ.2017.05.555668.

V. Venkateswarlu, P. V. Seshaiah, P. Arun, P. C. Behra, “A Study on Water Quality Parameters in Shrimp L. vannamei Semi-Intensive Grow Out Culture Farms in Coastal Districts of Andhra Pradesh, India”, International Journal of Fisheries and Aquatic Studies, vol. 7, no. 4, July 2019, pp. 394-399, https://www.fisheriesjournal.com/archives/2019/vol7issue4/PartF/7-4-64-509.pdf.

Technology Innovation Management & Entrepreneurship Information Service, “Prawn Farming”, September 2019, https://www.techno-preneur.net/technology/project-profiles/food/Prawn.htm.

K. Alagu, “The Importance of Water Quality in Shrimp Farming”, LinkedIn, February 2020, https://www.linkedin.com/pulse/importance-water-quality-shrimp-farming-kaliaperumal-alagu/.

Xukyo, “Raspberry Pi 3B+ Microcontroller Overview”, AranaCorp, February 2024, https://www.aranacorp.com/en/raspberry-pi-3b-microcontroller-overview/.

A. Ibbett, “An Examination of Real-World Data Leakage from IoT Devices”, Doctoral Thesis, School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, Australia, August 2022.

C. H. Chen, Y. C. Wu, J. X. Zhang, Y. H. Chen, “IoT-Based Fish Farm Water Quality Monitoring System,” Sensors, vol. 22, no. 17, September 2022, https://doi.org/10.3390/s22176700.

L. Parra, S. Sendra, L. García, J. Lloret, “Design and Deployment of Low-Cost Sensors for Monitoring the Water Quality and Fish Behavior in Aquaculture Tanks during the Feeding Process,” Sensors, vol. 18, no. 3, March 2018, https://doi.org/10.3390/s18030750.

N. A. Razman, W. Z. Wan Ismail, M. H. Abd Razak, I. Ismael, J. Jamaludin, “Design and Analysis of Water Quality Monitoring and Filtration System for Different Types of Water in Malaysia,” International Journal of Environmental Science and Technology, vol. 20, June 2022, pp. 3789-3800, https://doi.org/10.1007/s13762-022-04192-x.

O. O. Olanubi, T. T. Akano, O. S. Asaolu, “Design and development of an IoT-based intelligent water quality management system for aquaculture,” Journal of Electrical Systems and Information Technology, vol. 11, March 2024, https://doi.org/10.1186/s43067-024-00139-z.

H. Mahmud, M. A. Rahaman, S. Hazra, S. Ahmed, “IoT Based Integrated System to Monitor the Ideal Environment for Shrimp Cultivation with Android Mobile Application,” European Journal of Information Technologies and Computer Science, vol. 3, no. 1, February 2023, pp. 22-27, https://doi.org/10.24018/compute.2023.3.1.89.

K. L. Tsai, L. W. Chen, L. J. Yang, H. J. Shiu, H. W. Chen, “IoT Based Smart Aquaculture System with Automatic Aerating and Water Quality Monitoring,” Journal of Internet Technology, vol. 23, no. 1, January 2022, pp. 177-184, https://doi.org/10.53106/160792642022012301018.

M. C. Chiu, W. M. Yan, S. A. Bhat, N. F. Huang, “Development of Smart Aquaculture Farm Management System Using IoT and AI-based Surrogate Models,” Journal of Agriculture and Food Research, vol. 9, September 2022, https://doi.org/10.1016/j.jafr.2022.100357.

N. Ya’acob, N. N. S. N. Dzulkefli, A. L. Yusof, M. Kassim, N. F. Naim, S. S. M. Aris, “Water Quality Monitoring System for Fisheries Using Internet of Things (IoT),” IOP Conference Series: Materials Science and Engineering, vol. 1176, March 2021, https://doi.org/10.1088/1757-899X/1176/1/012016.

M. N. M. Yasin, M. M. A. M. Hamzah, M. Kassim, N. Arbain, “Freshwater pH Level Control and GUI System for Prawn Breeding,” International Journal of Advanced Trends in Computer Science and Engineering, vol. 9, no. 4, July 2020, pp. 5154-5160, https://doi.org/10.30534/ijatcse/2020/250942020.

A. G. Orozco-Lugo, D. C. McLernon, M. Lara, S. A. R. Zaidi, B. J. González, O. Illescas, C. I. Pérez-Macías, V. Nájera-Bello, J. A. Balderas, J. L. Pizano-Escalante, C. Mex Perera, R. Rodríguez-Vázquez, “Monitoring of Water Quality in a Shrimp Farm Using a FANET,” Internet of Things, vol. 18, May 2022, https://doi.org/10.1016/j.iot.2020.100170.

Autodesk, Inc., “IoT in Water — 4 Ways to Make Sense of Your Data,” Water Online, October 2020, https://www.wateronline.com/doc/iot-in-water-ways-to-make-sense-of-your-data-0001.

P. Van Wyk and J. Scarpa, “Water Wuality Requirements and Management,” in Farming Marine Shrimp in Recirculating Freshwater Systems,” Harbor Branch Oceanographic Institution, 1999, pp. 141-161.

M. S. Uddin, M. F. Istiaq, M. Rasadin, M. R. Talukder, “Freshwater Shrimp Farm Monitoring System for Bangladesh Based on Internet of Things,” Engineering Reports, vol. 2, no. 7, June 2020, https://doi.org/10.1002/eng2.12184.

Downloads

Published

2024-09-30

How to Cite

Data-Driven Water Monitoring System with Descriptive Analytics for Aquaculture Prawn Farms. (2024). Journal of Innovative Technology Convergence, 6(3). https://doi.org/10.69478/JITC2024v6n3a08