Temperature and Humidity Monitoring in Hydroponic Cultivation Based on Internet of Things: Dataset Development for Smart Agriculture

Authors

  • Simon Prananta Barus Informatics Study Program, Faculty of Science, Computers and Mathematics, Matana University
  • Jeriko Ichtus Seo Informatics Study Program, Faculty of Science, Computers and Mathematics, Matana University

DOI:

https://doi.org/10.32736/sisfokom.v14i1.2346

Keywords:

Dataset, Humidity, Internet of Things, Monitoring, Temperature

Abstract

This research is a continuation of the previous research, entitled "Development of Hydroponic Application based on Web and Internet of Things for the Community to Monitor pH and Total Dissolved Solids." Not only pH and Total Dissolved Solids (TDS) need to be monitored, but also temperature and humidity. This research aims to produce a temperature and humidity monitoring application (in addition to pH and TDS which already exist) in hydroponic cultivation and complete the dataset that supports smart agriculture. The research method includes literature study, hardware development using NodeMCU ESP8266 microcontroller and DHT11 sensor, web-based software development with JavaScript on the Front-End side, PHP on the Back-End side, Apache as Web Server, and MySQL as database management system (DBMS), as well as the implementation stage, integration, system testing and report writing. The results of the research show that the developed system can monitor temperature and humidity in real-time with a good level of accuracy. Not only that, this system can produce a hydroponic dataset that includes temperature and humidity parameters, which can be used for data analysis and improvement of hydroponic management. Thus, this study successfully expanded the scope of the hydroponic monitoring system by adding temperature and humidity parameters. This study contributes to optimizing the hydroponic cultivation system and supporting the development of data-based smart agriculture. Further research will integrate more monitoring parameters, conduct direct hydroponic cultivation trials, and apply artificial intelligence such as machine learning and deep learning to improve efficiency and effectiveness in hydroponic cultivation.

References

G. Rajaseger et al., “Hydroponics: current trends in sustainable crop production,” Bioinformation, vol. 19, no. 9, pp. 925–938, Sep. 2023, doi: 10.6026/97320630019925.

S. Barus, M. Tangdililing, P. A. Widjaya, S. Sujanto, and N. Jong, “PENERAPAN METODE HIDROPONIK PADA DESA BENTENG MAMULLU TANAH TORAJA UNTUK MENGATASI KEBUTUHAN SAYUR MAYUR”, Universal Raharja Community (URNITY Journal), vol. 3, no. 1, pp. 31-36, Feb. 2023.

P. Digital, “Kementan Dukung Ketahanan Pangan melalui Hidroponik,” Tempo, Jun. 15, 2022. Available: https://bisnis.tempo.co/read/1602065/kementan-dukung-ketahanan-pangan-melalui-hidroponik.

"Goal 2 | Department of Economic and Social Affairs.” Available: https://sdgs.un.org/goals/goal2.

U. Shareef, A. U. Rehman, and R. Ahmad, “A Systematic Literature Review on Parameters Optimization for Smart Hydroponic Systems,” AI, vol. 5, no. 3, pp. 1517–1533, Aug. 2024, doi: 10.3390/ai5030073

R. Raimarda, “Pengaruh Suhu dan Kelembapan pada Tumbuhan Halaman all - Kompas.com,” KOMPAS.com, Oct. 09, 2020. Available: https://www.kompas.com/skola/read/2020/10/09/223258169/pengaruh-suhu-dan-kelembapan-pada-tumbuhan?page=all

S. P. Barus and Y. A. Dhamma, “Development of Hydroponic Application based on Web and Internet of Things for The Community to Monitor pH and Total Dissolved Solids,” International Journal of Research in Community Service, vol. 5, no. 3, pp. 130–137, Jul. 2024, doi: 10.46336/ijrcs.v5i3.708.

D. Y. Setyawan, W. Warsito, R. Marjunus, and S. Sumaryo, “Automasi dan Internet of Things (IoT) pada Pertanian Cerdas: review artikel pada Jurnal Terakreditasi Kemenristek,” Setyawan | Prosiding Semnastek, Jun. 26, 2024. https://jurnal.umj.ac.id/index.php/semnastek/article/view/22702/10492 .

G. S. Patel, A. Rai, N. N. Das, and R. P. Singh, Smart Agriculture: Emerging Pedagogies of Deep Learning, Machine Learning and Internet of Things. CRC Press, 2021.

alldatasheet.com, “DHT11 Download.” Available: https://www.alldatasheet.com/datasheet-pdf/download/1440068/ETC/DHT11.html .

S. P. Barus, “Implementation of the PATAS model in the development of the Matana University Graduation Information System,” JISA(Jurnal Informatika Dan Sains), vol. 5, no. 2, pp. 116–119, Dec. 2022, doi: 10.31326/jisa.v5i2.1327.

B. Haryanto, N. Ismail, and E. J. Pristianto, “Sistem Monitoring Suhu dan Kelembapan Secara Nirkabel pada Budidaya Tanaman Hidroponik,” JTERA (Jurnal Teknologi Rekayasa), vol. 3, no. 1, p. 47, Jun. 2018, doi: 10.31544/jtera.v3.i1.2018.47-54.

R. M. Abdurrohman, “Prototipe monitoring suhu dan kelembapan secara realtime,” Journal ICTEE, vol. 4, no. 2, p. 29, Aug. 2023, doi: 10.33365/jictee.v4i2.3158.

D. C. M. Wijaya, H. Khariono, M. R. Abrori, R. A. Fernanda, and H. A. Kusuma, “Sistem Pemantauan Suhu dan Kelembapan Udara Pada Tanaman Hias Janda Bolong Terintegrasi,” Informatik Jurnal Ilmu Komputer, vol. 17, no. 3, p. 174, Jan. 2022, doi: 10.52958/iftk.v17i3.3436.

S. K. Risandriya, “Pemantauan dan Pengendalian Kelembapan, Suhu, dan Intensitas Cahaya Tanaman Tomat dengan Logika Fuzzy Berbasis IoT,” Journal of Applied Electrical Engineering, vol. 3, no. 1, pp. 9–14, Jun. 2019, doi: 10.30871/jaee.v3i1.1394.

S. D. Putra, H. Heriansyah, E. F. Cahyadi, K. Anggriani, and M. H. I. S. Jaya, “Development of smart hydroponics system using AI-based sensing,” JURNAL INFOTEL, vol. 16, no. 3, Aug. 2024, doi: 10.20895/infotel.v16i3.1190.

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Published

2025-01-31

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