Water Quality Control System In Goldfish Aquarium Using Fuzzy Method

Rizky Rizwansyach; Isa Hafidz; Chaironi Latif

doi:10.52435/complete.v6i1.681

Authors

Rizky Rizwansyach Electrical Engineering Study Program, Telkom University, Surabaya Campus, Jl. Ketintang No.156, Surabaya 60231, East Java, Indonesia
Isa Hafidz Electrical Engineering Study Program, Telkom University, Surabaya Campus, Jl. Ketintang No.156, Surabaya 60231, East Java, Indonesia
Chaironi Latif Electrical Engineering Study Program, Telkom University, Surabaya Campus, Jl. Ketintang No.156, Surabaya 60231, East Java, Indonesia

DOI:

https://doi.org/10.52435/complete.v6i1.681

Keywords:

Fuzzy, Goldfish, Turbidity, PH Water, Water pump

Abstract

Considering the beauty and unique characteristics of goldfish as ornamental fish, keeping goldfish in an aquarium is a popular hobby among the community. However, some people face challenges in maintaining goldfish that must be controlled manually. In this work, the author proposes to create a water quality control system for goldfish aquariums using fuzzy logic. This system uses the E-201-C pH sensor to measure the water's pH level, the SEN-0189 turbidity sensor to detect water turbidity, an ultrasonic sensor to maintain water height, and the ESP32 as the microcontroller. In the pH control, a mini pump is used, which activates when the pH level is >9 to lower the water's pH to the set point. Meanwhile, for controlling water turbidity, two 12V DC pumps are used, where one pump functions to discharge turbid water and the other to fill with clean water. The data read by the sensor can be monitored through the OLED screen. Based on the test results, the water quality control system for the goldfish aquarium using the fuzzy method can function well. Meanwhile, the water draining process takes 5 minutes and 20 seconds, and the clean water filling takes about 15 minutes and 24 seconds.

References

A. F. Nurzaman, M. Wildan, and N. Anisa, “Development of Internet of Things System for Smart Fishery in Ornamental Fish Farming,” in Proceedings of 2023 International Conference on Information Management and Technology, ICIMTech 2023, 2023. doi: 10.1109/ICIMTech59029.2023.10277831.

M. Yazdanmanesh, K. Tadayon, D. Bagherian Koshkghazi, and N. Mosavari, “Isolation and identification of non-tuberculous mycobacteria from aquarium fish in Ilam, Iran,” J. Clin. Tuberc. Other Mycobact. Dis., vol. 37, 2024, doi: 10.1016/j.jctube.2024.100478.

M. Cleal, A. Gibbon, B. D. Fontana, and M. O. Parker, “The importance of pH: How aquarium water is affecting behavioural responses to drug exposure in larval zebrafish,” Pharmacol. Biochem. Behav., vol. 199, 2020, doi: 10.1016/j.pbb.2020.173066.

K. L. Onthank et al., "The Open acidification Tank Controller: An open-source device for the control of pH and temperature in ocean acidification experiments," HardwareX, vol. 14, 2023, doi: 10.1016/j.ohx.2023.e00435.

N. L. Manuel, N. Inanc, and M. Luy, “Control and performance analyses of a DC motor using optimized PIDs and fuzzy logic controller,” Results Control Optim., vol. 13, 2023, doi: 10.1016/j.rico.2023.100306.

L. Zhang, “A Deployment and Coverage Optimization Algorithm for Self-Powered Wireless Sensor Networks Based on Hybrid Swarm Intelligence,” IEEE Sens. J., vol. 23, no. 18, 2023, doi: 10.1109/JSEN.2022.3230955.

H. R. Axelrod, Encyclopedia of Aquarium Fish. Neptune City, New Jersey: TFH Publications, 2005.