Designing Water Quality Monitoring Application Using Esp8266
Abstract
Water is the main need for human life. The decline in water quality due to household, industrial, and environmental waste requires a monitoring system that is able to work quickly, sustainably, and accurately. Continuous monitoring of water quality has an important role in supporting effective water resource management. This research develops an Internet of Things (IoT)-based water quality monitoring system by utilizing ESP8266 microcontrollers. IoT-based water quality monitoring systems in aquascapes are able to control the temperature and pH of the water so that they remain within the ideal range for fish life. In this study, how to design and build an Internet of Things based water quality monitoring system using ESP8266 microcontroller. The developed system is expected to be able to read water quality parameters in the form of pH values and water turbidity levels in real-time through integrated sensors, then send the data to the IoT monitoring application and Telegram notifications so that it can be easily accessed by users. Thus, the developed system is suitable for IoT-based water quality monitoring.
Downloads
References
A. Kurniawan, & H. A. Lestari, . (2020). Nutrient control system of floating hydroponic system kale (Ipomea reptans) using Telegram-based Internet of Things. Journal of Agricultural Engineering Lampung, vol. 9, no. 4,, 326-335.
A. Mulia, et al. (2024). AQUAMONITOR: An Internet of Things (IoT)-based water quality monitoring system using NodeMCU V3 ESP8266. JITET (Journal of Applied Electrical Informatics and Engineering), vol. 14, no. 1.
A. Rahman, & A. N. Salim, . (2022). Aquascape water pH and turbidity control system using IoT-based Wemos D1 Mini ESP8266. Journal of Integrated Technology, vol. 8, no. 1, pp. 22–30, 2022., 22-30.
A. Taufik, & A. Fadlil, ". (2023). Internet of Things based on the Internet of Things pH and turbidity monitoring system for koi fish ponds using the Blynk application. Journal of Electrical Engineering, vol. 14, no. 1, pp. 56–61, Jan. 2023, 56–61.
E. Febriarta, & M. Widyastuti. (2020). A study of groundwater quality due to the impact of intrusion in some coastal areas of Tuban Regency. Journal of Geography, vol. 17, no. 2, 39-48.
E. Marianis, et al. (2022). Turbidity and water temperature monitoring system in freshwater ornamental fish aquariums based on IoT (Internet of Things). Scientific Magazine of Electrical Technology, vol. 21, no. 2.
F. Febriansyah , & R. Sibarani, . (2024). Design of a device to detect the level of water turbidity and water drain in aquariums. Journal of Satya Informatics, vol. 9, no. 1, pp. 45–53, May 2024., 45-53.
H. P. Ramadhan, et al. (2020). Monitoring the water quality of shrimp ponds using the data logging method. Journal of Informatics and Information Systems Engineering, vol. 6, no. 1.
Haryanto, et al. (2021). Design and build a water quality monitoring system (pH and turbidity) in an Internet of Things based aquarium. GO INFOTECH, vol. 27, no. 2.
I. Saraswati, et al. (2025). The design of the water clarity monitoring system uses turbidity sensors in reservoirs based on the Internet of Things. Scientific Journal of Strangling, vol. 14, no. 1, 92-100.
J. P. Hapsari, et al. (2024). An Internet of Things (IoT) water quality monitoring system. Journal of Electrical and Computational Engineering (ELKOM), vol. 6, no. 2, 144-153.
M. D. Kainama , & H. D. Purnomo, ". (2025). Implementation of IoT-based water quality monitoring system in spring reservoirs in the Larier Ambon area. AITI: Journal of Information Technology, vol. 22, no. 2, 206-220.
M. K. Ikhsan, et al. (2024). Implementation of IoT-based water pH filtering monitoring and controlling system using NodeMCU and Telegram. Journal of TGD Computer Systems, vol. 3, no. 1, 1–12.
N. Rohman, et al. (2025). Automatic water monitoring and refilling system based on water discharge and quality in IoT-based NFT hydroponics. Global Research and Innovation Journal (GREAT), vol. 1, no. 2, 2865–2874.
P. Wms, , & et al. (2023). TDS, pH, and COD analysis to determine the water quality of the residents of Ciliayung Village. Journal of Physics Unpad, vol. 12, no. 2, 43-49.
R. Anjani, & E. Fitriani, ". (2025). IoT-based clean water consumption monitoring system using water flow and quality sensors with Arduino and Blynk. Rang Engineering Journal, vol. 8, no. 2, Jun. 2025.
S. Anzjarwati, et al. (2023). Preparation of TDS, pH, and total coliform levels in the processing of rainwater into ready-to-drink water. Journal of Wetland Environmental Technology, vol. 9, no. 3, pp. 429–438, 2023., 429-438.
T. Rikanto, & A. Witanti, . (2021). Internet of Thing-based water turbidity quality monitoring system. Fasilkom Journal, vol. 11, no. 2, pp. 87–90, Dec. 2021., 87-90.
Y. Karmani, et al. (2022). IoT-based system monitoring water turbidity level and fish feeding in aquariums. Journal of Information Technology, vol. 6, no. 1.
Joisce, Hanum Putri Kamelianti, & Rizal Aprianto. (2025). Concept And Potential For The Implementation Of Smart Parking System In Indonesia: A Literature Review . JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 467 - 481. https://doi.org/10.36378/jtos.v8i2.4647
Fariz, Eka Dyar Wahyuni, & Tri Luhur Indayanti Sugata. (2025). Implementation of the FP-Growth Algorithm for Bundling Strategy and Store Layout Redesign at Toko Kasih Ibu. JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 482 - 494. https://doi.org/10.36378/jtos.v8i2.4673
Windy Fadhilah Susanti, Ana Wati, S. F., & Indayanti Sugata, T. L. (2025). UI/UX Design of the “PrintOn!” Printing Services Marketplace for UMKM Photocopying and Printing Businesses Using the User Centered Design Method. JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 495 - 505. https://doi.org/10.36378/jtos.v8i2.4688
Kartika, A. D. P., Anindo Saka Fitri, & Nambi Sembilu. (2025). Developing a Web-Based Printing Transaction System Using The Prototype Method: A Case Study at Amanah Advertising. JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 514 - 528. https://doi.org/10.36378/jtos.v8i2.4692
Irawan, Y., Refni Wahyuni, & Herianto. (2025). An Integrated Machine Learning and Deep Learning Approach for Multiclass Flood Risk Classification with Feature Selection and Imbalanced Data Handling. JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 650 - 661. https://doi.org/10.36378/jtos.v8i2.4639
Revina Pravita Sari, Karnadi, & Jimmie. (2025). Applying the Waterfall method to build applications E-Commerce at Palembang City Computer Embroidery Partners. JURNAL TEKNOLOGI DAN OPEN SOURCE, 8(2), 1243 - 1256. https://doi.org/10.36378/jtos.v8i2.5199
Copyright (c) 2026 Revi Margelia, Muhammad Ihsan
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License which permits unrestricted use, distribution, and reproduction in any medium. Users are allowed to read, download, copy, distribute, search, or link to full-text articles in this journal without asking by giving appropriate credit, provide a link to the license, and indicate if changes were made. All of the remix, transform, or build upon the material must distribute the contributions under the same license as the original.
