IoT-Enabled Smart Hydroponic System Using Nutrient Film Technique for Precision Agriculture
Abstract
The study aims to develop an IoT-enabled automated hydroponic system using the Nutrient Film Technique (NFT) to optimize plant growth with minimal human intervention. The system integrates sensors, microcontrollers, and cloud-based monitoring to maintain optimal conditions for crops. The system utilizes Arduino Uno, ESP8266 Wi-Fi module, and sensors including pH, TDS, DHT11 and water level sensors. Data collected from these sensors is processed in real time, allowing automated adjustments through relay-controlled water and nutrient pumps. The system transmits data to the Thing-Speak IoT platform, enabling remote monitoring and predictive analytics. The proposed hydroponic system ensures stable environmental conditions, improving plant growth efficiency. Key parameters such as pH, TDS levels and humidity are maintained within optimal ranges. The automated system reduces manual intervention, enhances water and nutrient efficiency, and increases yield consistency compared to traditional farming methods. The IoT-based NFT hydroponic system demonstrates significant potential in urban agriculture and controlled environment farming. By leveraging automation, AI-driven analytics, and cloud-based monitoring, it provides a scalable and sustainable solution for precision farming. Future advancements may include AI-based predictive analytics, solar-powered energy solutions, and robotic automation for further optimization.
Keywords
Full Text:
PDFReferences
S. Pawar, S. Tembe, R. Acharekar, S. Khan, and S. Yadav, “Design of an IoT enabled Automated Hydroponics system using NodeMCU and Blynk,” in 2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019, pp. 1-6.
M. F. Saaid, A. Sanuddin, M. Ali, and M. S. A. I. M. Yassin, “Automated pH controller system for hydroponic cultivation,” in 2015 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), 2015, pp. 186-190.
D. S. Domingues, H. W. Takahashi, C. A. Camara, and S. L. Nixdorf, “Automated system developed to control pH and concentration of nutrient solution evaluated in hydroponic lettuce production,” Computers and Electronics in Agriculture, vol. 84, pp. 53-61, 2012.
O. Elijah, T. A. Rahman, I. Orikumhi, C. Y. Leow, and M. N. Hindia, “An overview of Internet of Things (IoT) and data analytics in agriculture: Benefits and challenges,” IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3758-3773, 2018.
F. Kiani and A. Seyyedabbasi, “Wireless sensor network and internet of things in precision agriculture,” in 2018 4th International Conference on Computer and Technology Applications (ICCTA), 2018, pp. 1-5.
A. A. Kori, K. N. Veena, P. I. Basarkod, and R. Harsha, “Hydroponics System based on IoT,” Annals of the Romanian Society for Cell Biology, vol. 25, pp. 9683-9688, 2021.
I. Ezzahoui, R. A. Abdelouahid, K. Taji, and A. Marzak, “Hydroponic and aquaponic farming: Comparative study based on Internet of Things (IoT) technologies,” Procedia Computer Science, vol. 191, pp. 499-504, 2021.
V. Kanagaraj, G. Nareshbabu, D. N. Chandni, J. K. Sr., and K. Sankar, “Design and development of an automated hydroponics system based on IoT with data logging,” in 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2023.
S. Jain, M. Alam, and M. Bokhari, “Future hydroponic systems using IoT for sustainable agriculture,” in Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development (ICIDSSD), 2020.
A. Kumar and S. Dassan, “Monitoring and accelerating plant growth using IoT and hydroponics,” in International Conference on Computer Communication and Informatics (ICCCI), 2023.
T. R. Gururani, A. T. Upadhyaya, and M. Kumar, “A review on smart agriculture: IoT based monitoring and automation of hydroponic farms,” IEEE Access, vol. 10, pp. 56379-56401, 2022.
Y. Lu, H. Zhang, and L. Yu, “AI-enabled IoT-based smart hydroponics farming system,” in 2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTIS), 2022, pp. 214-219.
H. Wu and Y. Wang, “Optimization of hydroponic nutrient film technique system using deep learning,” IEEE Transactions on Automation Science and Engineering, vol. 19, no. 4, pp. 2401-2413, 2023.
A. Ghosh and S. Sinha, “IoT-based smart hydroponic system using machine learning for optimized growth,” in 2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), 2023.
X. Zhang, J. Wang, and S. Lee, “Cloud-based IoT-enabled hydroponic farming for real-time monitoring and control,” IEEE Sensors Journal, vol. 23, no. 12, pp. 14563-14572, 2023.
M. S. El-Sayed and A. Hassan, “Smart hydroponic system using IoT for controlled environment agriculture,” in 2022 IEEE Green Technologies Conference (GreenTech), 2022, pp. 45-50.
P. Sharma, V. Kumar, and R. Mishra, “Precision agriculture using IoT-enabled hydroponics,” in 2021 IEEE Conference on Sustainable Energy and Intelligent Systems (SEIS), 2021, pp. 78-84.
J. Lin and B. Patel, “Energy-efficient IoT-based vertical farming using hydroponic systems,” IEEE Transactions on Smart Agriculture, vol. 2, no. 3, pp. 203-214, 2022.
Y. Z. Luo and J. X. Zhang, “Blockchain-based data security in IoT-enabled hydroponic farming,” in 2023 IEEE Symposium on Cybersecurity and IoT (SCI), 2023, pp. 129-135.
C. Wang and L. K. Tan, “Automated hydroponic system with nutrient monitoring and pH control using IoT,” in 2021 IEEE International Conference on Artificial Intelligence in Agriculture (AIIA), 2021, pp. 56-63.
S. Ali, N. Patel, and K. Singh, “Cloud-assisted hydroponics: A scalable approach for sustainable farming,” in 2022 IEEE International Conference on IoT and Cloud Computing (ICCC), 2022, pp. 312-319.
P. R. Das and M. K. Behera, “Comparative study of IoT-based smart hydroponic farming systems,” in 2023 IEEE Conference on Intelligent Systems and Sustainable Agriculture (ISSA), 2023, pp. 71-78.
R. Krishnan and T. J. Mathew, “AI and IoT integration in hydroponic agriculture: Challenges and future directions,” IEEE Internet of Things Journal, vol. 11, no. 2, pp. 3451-3465, 2024.
A. H. Roy and K. B. Sharma, “Deep learning for hydroponic farming: A predictive analytics approach,” in 2023 IEEE International Conference on Artificial Intelligence and Applications (AIA), 2023, pp. 87-94.
M. N. Patel and J. R. Lewis, “Hydroponics and IoT: A review on real-time plant monitoring and automation,” in 2022 IEEE International Conference on Smart Agriculture (ICSA), 2022, pp. 101-108.
DOI: http://doi.org/10.11591/ijict.v15i2.pp900-908
Refbacks
- There are currently no refbacks.
Copyright (c) 2026 Institute of Advanced Engineering and Science
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The International Journal of Informatics and Communication Technology (IJ-ICT)
p-ISSN 2252-8776, e-ISSN 2722-2616
This journal is published by the Intelektual Pustaka Media Utama (IPMU).