Design and Build Telecontroling Temperature and Water Quality of Turtle Aquascapes Based on Fuzzy Logic

Authors

  • Amar Farrichil Ayyubi Politeknik Negeri Malang
  • Azam Muzakhim Imammuddin Politeknik Negeri Malang
  • Mila Kusumawardani Politeknik Negeri Malang

DOI:

https://doi.org/10.33795/jartel.v14i3.4120

Keywords:

Aquascape, ESP32, Internet of Things, turtle monitoring system, water level sensor, water quality monitoring, water turbidity sensor, water temperature sensor

Abstract

Aquascape is one of the media for water pets that is quite popular during the pandemic. One of the animals that can be kept with aquascape media is a turtle. Maintenance of turtles in aquascapes requires accuracy and persistence in maintaining water quality in aquascapes to have stable conditions for turtles in them. Temperature, turbidity and water level are some of the parameters that need to be considered in order for turtles to survive in the aquascape. Thus, we need a technology that has a function as a monitoring of temperature, turbidity and water level as well as having a direct connection to the user. In this study, the use of the DS18B20 temperature sensor, water turbidity sensor and ultrasonic sensor as a water level meter has a connection that is connected to the user using ESP32. In addition, the existence of pumps, filters and water coolers can support the quality of water in the aquascape to be maintained either automatically or manually. The results of this study indicate that the existence of this system can maintain the quality of water in the aquascape in real time to the user. This is demonstrated by three sensors that have a 98% accuracy level so that it can turn on the output components well. The three sensors also have delays of 240.006315 ms and are in the category

References

H. Yoon, J. Kim, and S. Park, “Smart water quality monitoring system using IoT,” Sensors, vol. 20, no. 21, Art. no. 6102, 2020.

M. R. Alam, M. M. Hassan, and A. Alelaiwi, “A cloud-based IoT framework for fish pond water quality monitoring,” Future Generation Computer Systems, vol. 105, pp. 742–753, 2020.

S. Li, L. D. Xu, and S. Zhao, “IoT for smart water systems: Architecture, applications, and challenges,” Future Generation Computer Systems, vol. 108, pp. 845–856, 2020.

A. A. Abouelsaad, A. A. Moussa, and M. S. Sayed, “IoT-based water quality monitoring system using ESP32,” IEEE Access, vol. 8, pp. 119567–119579, 2020.

A. K. Sharma and P. Kumar, “Energy-efficient IoT-based monitoring systems for smart environments,” IEEE Access, vol. 8, pp. 202028–202048, 2020.

Y. Wang, X. Wang, and J. Chen, “Solar-powered wireless sensor networks for environmental and water monitoring,” Sensors, vol. 20, no. 6, Art. no. 1725, 2020.

L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965.

K. M. Passino and S. Yurkovich, Fuzzy Control. Reading, MA, USA: Addison-Wesley, 1998.

R. M. Rahman, M. M. Hasan, and M. R. Islam, “Design of fuzzy logic controller for water level control,” International Journal of Fuzzy Systems, vol. 22, no. 2, pp. 450–461, 2020.

Y. Liu, J. Wang, and X. Zhang, “Fuzzy logic-based temperature control system for aquatic environments,” Applied Soft Computing, vol. 96, Art. no. 106672, 2020.

R. K. Kodali and A. Naikoti, “ESP32 based smart water quality monitoring system,” International Journal of Electrical and Computer Engineering, vol. 11, no. 1, pp. 451–459, 2021.

S. Wu, H. Liu, and Y. Zhao, “Low-power IoT architecture for environmental monitoring systems,” Sensors, vol. 21, no. 3, Art. no. 902, 2021.

A. Rahman et al., “IoT-based real-time water level and turbidity monitoring system,” Applied Sciences, vol. 11, no. 8, Art. no. 3567, 2021.

M. S. Mahmoud and A. A. Hossam-Eldin, “Smart water management systems using IoT and fuzzy control,” Sustainable Computing: Informatics and Systems, vol. 30, Art. no. 100518, 2021.

J. Gubbi et al., “Internet of Things (IoT): A vision, architectural elements, and future directions,” Future Generation Computer Systems, vol. 113, pp. 1–13, 2021.

H. Wang, Z. Li, and M. Sun, “Performance analysis of IoT-based water monitoring systems,” IEEE Access, vol. 10, pp. 12234–12246, 2022.

P. Rossi et al., “Energy-aware IoT systems for environmental monitoring,” Sensors, vol. 22, no. 9, Art. no. 3475, 2022.

Y. Chen et al., “Cloud-based monitoring and control of aquatic systems using IoT,” Journal of Cloud Computing, vol. 11, Art. no. 34, 2022.

A. Putra, R. Wijaya, and D. Kurniawan, “Fuzzy logic-based smart aquaculture monitoring system,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 28, no. 3, pp. 1321–1330, 2022.

M. Al-Saidi and K. Elshafei, “Intelligent IoT systems for water quality management,” Journal of Cleaner Production, vol. 389, Art. no. 136061, 2024.

Downloads

Published

30-09-2024

How to Cite

Ayyubi, A. F., Imammuddin, A. M., & Kusumawardani, M. (2024). Design and Build Telecontroling Temperature and Water Quality of Turtle Aquascapes Based on Fuzzy Logic. JURNAL JARTEL: Jurnal Jaringan Telekomunikasi, 14(3), 260–267. https://doi.org/10.33795/jartel.v14i3.4120