Design and Development of an ESP32-Based IoT System for Hydroponic Nutrient Monitoring and Control
DOI:
https://doi.org/10.67795/jesai.v1i1.8Keywords:
ESP32, hydroponics, Internet of Things (IoT) , monitoring, nutrient control, ThingsBoardAbstract
Nutrient solution monitoring and control are essential aspects of hydroponic cultivation because they directly influence plant growth. Conventional monitoring methods require continuous manual observation, making the cultivation process less efficient. This study aims to design and implement an Internet of Things (IoT)-based hydroponic nutrient monitoring and control system using an ESP32 microcontroller integrated with a Total Dissolved Solids (TDS) sensor, a pH sensor, and a DS18B20 temperature sensor. Measurement data are transmitted in real time to the ThingsBoard platform via the MQTT protocol, enabling remote monitoring and control through a web-based dashboard. The proposed system is also equipped with an automatic nutrient dosing mechanism using a peristaltic pump based on predefined nutrient concentration setpoints. Sensor performance was evaluated by comparing the measurement results with reference instruments and analyzed using statistical parameters, including the mean, standard deviation, Root Mean Square Error (RMSE), and mean error. The experimental results show that the DS18B20, TDS, and pH sensors achieved mean errors of 0.58%, 0.20%, and 1.75%, respectively, with RMSE values of 0.16 °C, 1.95 ppm, and 0.12 pH, indicating good agreement with the reference instruments. Furthermore, the system successfully performed real-time monitoring of nutrient solution parameters, executed automatic nutrient control according to the programmed control logic, and stored and exported monitoring data to Microsoft Excel. These results demonstrate that the proposed system operates as intended and is suitable for real-time hydroponic nutrient monitoring and control applications based on the Internet of Things (IoT).
References
[1]. N. Nurjaya, G. A. Mahendra, and I. N. Yarman, “Innovation of Smart Agricultural Control System in NFT Hydroponic based on Artificial Intelligence of Things,” Eduvest – Journal of Universal Studies, vol. 2, no. 1, pp. 183–194, Jan. 2022.
[2]. T. Hariono and M. C. Putra, "Data Acquisition for Monitoring IoT-Based Hydroponic Automation System Using ESP8266," NEWTON: Networking and Information Technology, vol. 1, no. 1, pp. 1–7, 2021.
[3]. R. Linelson and F. R. Saputri, "Design of a Nutrient and Environment Monitoring IoT Device in Vertical Hydroponic System," Ultima Computing: Jurnal Sistem Komputer, vol. 17, no. 1, 2025.
[4]. A. D. Purwanto, F. Supegina, and T. M. Kadarina, "Sistem kontrol dan monitor suplai nutrisi hidroponik sistem deep flow technique (DFT) berbasis Arduino NodeMCU dan aplikasi Android," Jurnal Teknologi Elektro, vol. 10, no. 3, pp. 152–158, Sept. 2019.
[5]. A. Y. H. Putra and W. S. Pambudi, "Sistem kontrol otomatis pH larutan nutrisi tanaman bayam pada hidroponik NFT (Nutrient Film Technique)," Jurnal Ilmiah Mikrotek, vol. 2, no. 4, pp. 11–20.
[6]. M. Faisal, A. N. Bachtiar, and M. Darwis, "IoT Implementation for Hydroponic Water Monitoring Using Web-Based pH and TDS Sensors with Node-Red," JISA (Jurnal Informatika dan Sains), vol. 8, no. 1, 2025.
[7]. W. Muhammad, L. Faridah, and Sutisna, "Automated Nutrient Control and Monitoring System for Internet of Things (IoT)-Based Hydroponic Towers," Jurnal Informatika dan Teknik Elektro Terapan, vol. 13, no. 3S1, 2025.
[8]. Espressif Systems, ESP32 Series Datasheet, Version 5.x, Espressif Systems, Shanghai, China, 2024.
[9]. DFRobot, Gravity: Analog pH Sensor/Meter Kit V1.1 (SKU: SEN0161-V2), Shanghai, China: DFRobot, 2024.
[10]. DFRobot, Gravity: Analog TDS Sensor/Meter V1.0, Shanghai, China: DFRobot, 2024.
[11]. Maxim Integrated, DS18B20 Programmable Resolution 1-Wire Digital Thermometer Datasheet, San Jose, CA, USA: Maxim Integrated, 2019.
[12]. M. Faisal, A. N. Bachtiar, and M. Darwis, "IoT Implementation for Hydroponic Water Monitoring Using Web-Based pH and TDS Sensors with Node-Red," JISA (Jurnal Informatika dan Sains), vol. 8, no. 1, 2025.
[13]. W. Muhammad, L. Faridah, and Sutisna, "Automated Nutrient Control and Monitoring System for Internet of Things (IoT)-Based Hydroponic Towers," Jurnal Informatika dan Teknik Elektro Terapan, vol. 13, no. 3S1, 2025.
[14]. OASIS, MQTT Version 3.1.1 Plus Errata 01, OASIS Standard, Dec. 2015
[15]. Willmott, C. J., & Matsuura, K. (2005). Advantages of the Mean Absolute Error (MAE) over the Root Mean Square Error (RMSE) in assessing average model performance. Climate Research, 30(1), 79–82.
[16]. DFRobot, Gravity: Analog TDS Sensor/Meter for Arduino (SKU: SEN0244) Wiki, DFRobot, Shanghai, China. [Online]. Available: https://wiki.dfrobot.com/Gravity_Analog_TDS_Sensor_Meter_For_Arduino-_SKU_SEN0244. Accessed: Jul. 27, 2026.
[17]. M. R. Shamshiri et al., "Nutrient Solution Temperature Affects Growth and °Brix Parameters of Seventeen Lettuce Cultivars Grown in an NFT Hydroponic System," Horticulturae, vol. 7, no. 9, Art. no. 321, 2021.
[18]. V. Vaštakaitė-Kairienė et al., "Precise Management of Hydroponic Nutrient Solution pH: The Effects of Minor pH Changes and MES Buffer Molarity on Lettuce Physiological Properties," Horticulturae, vol. 9, no. 7, Art. no. 837, 2023.
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Copyright (c) 2026 Muhammad Fauzi Damanik, Yulisman, Yulisman, Aggrivina Dwiharzandis, Dytchia Septi Kesuma, Ade Usra Berli
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