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22 July 2024
Reseach Article

Internet of Things based Automated Irrigation System for Growing Grapes

by Moechammad Sarosa, Erlita Putri Wahyu, Agil Evan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 1
Year of Publication: 2024
Authors: Moechammad Sarosa, Erlita Putri Wahyu, Agil Evan

Moechammad Sarosa, Erlita Putri Wahyu, Agil Evan . Internet of Things based Automated Irrigation System for Growing Grapes. International Journal of Computer Applications. 186, 1 ( Jan 2024), 44-48. DOI=10.5120/ijca2024923344

@article{ 10.5120/ijca2024923344,
author = { Moechammad Sarosa, Erlita Putri Wahyu, Agil Evan },
title = { Internet of Things based Automated Irrigation System for Growing Grapes },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2024 },
volume = { 186 },
number = { 1 },
month = { Jan },
year = { 2024 },
issn = { 0975-8887 },
pages = { 44-48 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2024923344 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T01:29:28.682810+05:30
%A Moechammad Sarosa
%A Erlita Putri Wahyu
%A Agil Evan
%T Internet of Things based Automated Irrigation System for Growing Grapes
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 1
%P 44-48
%D 2024
%I Foundation of Computer Science (FCS), NY, USA

Grape growing requires care and diligence in providing nutrients to feed the plants and watering according to the plants' needs to maximized growth. This research develops a system to meet these needs, namely a system for watering according to the needs of the plants, i.e. according to soil moisture. The moisture sensor is used to determine the water requirements of the plants, and when the sensor indicates that the water content in the planting medium is less than the specified value, the system delivers water to the planting medium. To know the nutrients needed by the plants, this system is equipped with an NPK sensor, and based on the readings of the NPK sensor, nutrients that are lacking in the planting medium are added by mixing nutrients with the water for irrigation. In order to monitor the development of the vines, this system has also been equipped with a camera so that the owners of the vines can take pictures of their plants using Android devices connected to the irrigation system using Internet of Thing technology. The results of the tests carried out show that. Based on the results and tests carried out on the irrigation system, several conclusions can be drawn, including the following: the irrigation system has been able to function properly using several sensor components, namely the soil moisture sensor, the NPK sensor and the camera module connected to the ESP8266 microcontroller. The average automatic watering time is ± 6 seconds, the soil moisture is ± 60% and the accuracy of the readings from each sensor is ± 99%. During the 30 days of testing, vine A (manual) experienced a growth of ± 4.3 cm while vine B (automatic) experienced a growth of ± 5.2 cm.

  1. A. G. E. Ausseil, R. M. Law, A. K. Parker, E. I. Teixeira, and A. Sood, “Projected Wine Grape Cultivar Shifts Due to Climate Change in New Zealand,” Front. Plant Sci., vol. 12, no. April, pp. 1–14, 2021, doi: 10.3389/fpls.2021.618039.
  2. B. Suter, A. Destrac Irvine, M. Gowdy, Z. Dai, and C. van Leeuwen, “Adapting Wine Grape Ripening to Global Change Requires a Multi-Trait Approach,” Front. Plant Sci., vol. 12, no. February, pp. 1–17, 2021, doi: 10.3389/fpls.2021.624867.
  3. J. M. Alston and O. Sambucci, “Grapes in the World Economy,” in Compendium of Plant Genomes, D. Cantu and M. A. Walker, Eds. Springer, Cham, 2019, pp. 1–24. doi:
  4. J. Silva and R. Uchida, “Essential Nutrients for Plant Growth :,” Plant Nutr. Manag. Hawaii’s Soils, Approaches Trop. Subtrop. Agric., pp. 31–55, 2000.
  5. O. Brendel, “The relationship between plant growth and water consumption: a history from the classical four elements to modern stable isotopes,” Ann. For. Sci., vol. 78, no. 2, 2021, doi: 10.1007/s13595-021-01063-2.
  6. J. Spanner, “Healthy soils are the basis for healthy food production,” Fao, 2015.
  7. P. Shrivastav et al., “Role of Nutrients in Plant Growth and Development,” in Contaminants in Agriculture, M. Naeem, A. A. Ansari, and S. S. Gill, Eds. Springer, Cham, 2020, pp. 43–59. doi:
  8. P. H. Brown, F. J. Zhao, and A. Dobermann, “What is a plant nutrient? Changing definitions to advance science and innovation in plant nutrition,” Plant Soil, vol. 476, no. 1–2, pp. 11–23, 2022, doi: 10.1007/s11104-021-05171-w.
  9. M. Bertamini and M. Faralli, “Late Pruning and Forced Vine Regrowth in Chardonnay and Pinot Noir: Benefits and Drawbacks in the Trento DOC Basin (Italy),” Agronomy, vol. 13, no. 5, 2023, doi: 10.3390/agronomy13051202.
  10. A. Pisciotta, E. Barone, and R. Di Lorenzo, “Table-Grape Cultivation in Soil-Less Systems : A Review,” Horticulturae, vol. 8, no. 6, p. 553, 2022, doi:
  11. S. T. Arab, T. Salari, R. Noguchi, and T. Ahamed, “Land Suitability Analysis for Grape (Vitis vinifera L.) Production Using Satellite Remote Sensing, GIS, and Analytical Hierarchy Process,” in New Frontiers in Regional Science: Asian Perspectives, T. Ahamed, Ed. Springer, Singapore, 2022, pp. 149–184. doi:
  12. A. Qu et al., “Research on Grape-Planting Structure Perception Method Based on Unmanned Aerial Vehicle Multispectral Images in the Field,” Agric., vol. 12, no. 11, 2022, doi: 10.3390/agriculture12111894.
  13. G. Lu, K. Zhang, Y. Que, and Y. Li, “Grapevine double cropping: a magic technology,” Front. Plant Sci., vol. 14, no. April, pp. 1–7, 2023, doi: 10.3389/fpls.2023.1173985.
  14. M. Y. Taskesenlioglu, S. Ercisli, M. Kupe, and N. Ercisli, “History of Grape in Anatolia and Historical Sustainable Grape Production in Erzincan Agroecological Conditions in Turkey,” Sustain., vol. 14, no. 3, 2022, doi: 10.3390/su14031496.
  15. M. Hardie, “Review of novel and emerging proximal soil moisture sensors for use in agriculture,” Sensors (Switzerland), vol. 20, no. 23, pp. 1–23, 2020, doi: 10.3390/s20236934.
  16. C. V. Bhaskar, A. Lakshmipriya, K. Hemapriya, A. Hemanthkumar, and V. T. Kireeti, “Soil Moisture Detection and Monitoring Through Iot,” J. Electron. Commun. Eng. Res., vol. 8, no. 4, pp. 10–13, 2022.
  17. Heye Reemt Bogena, Ansgar Weuthen, and Johan Alexander Huisman, “Recent Developments in Wireless Soil Moisture Sensing to Support Scientific Research and Agricultural Management,” Sensors, vol. 22, no. 9792, 2022.
  18. A. Bhujel et al., “Sensor Systems for Greenhouse Microclimate Monitoring and Control: a Review,” J. Biosyst. Eng., vol. 45, pp. 341–361, 2020, doi:
  19. E. Levintal, Y. Ganot, G. Taylor, P. Freer-Smith, K. Suvocarev, and H. E. Dahlke, “An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture,” Soil, vol. 8, no. 1, pp. 85–97, 2022, doi: 10.5194/soil-8-85-2022.
  20. M. Nadporozhskaya, N. Kovsh, R. Paolesse, and L. Lvova, “Recent Advances in Chemical Sensors for Soil Analysis: A Review,” Chemosensors, vol. 10, no. 1, 2022, doi: 10.3390/chemosensors10010035.
  21. J. L. C. Ison, J. A. B. S. Pedro, J. Z. Ramizares, G. V. Magwili, and C. C. Hortinela, “Precision Agriculture Detecting NPK Level Using a Wireless Sensor Network with Mobile Sensor Nodes,” in 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), 2021, pp. 1–6. doi: 10.1109/HNICEM54116.2021.9732000.
  22. X. Lu et al., “Reconstruction method and optimum range of camera-shooting angle for 3D plant modeling using a multi-camera photography system,” Plant Methods, vol. 16, no. 1, pp. 1–16, 2020, doi: 10.1186/s13007-020-00658-6.
  23. K. V. S. S. Ganesh, S. P. S. Jeyanth, and A. R. Bevi, “IOT based portable heart rate and SpO2 pulse oximeter,” HardwareX, vol. 11, p. e00309, 2022, doi: 10.1016/j.ohx.2022.e00309.
  24. M. W. Hasan, “Memories - Materials , Devices , Circuits and Systems Building an IoT temperature and humidity forecasting model based on long short-term memory ( LSTM ) with improved whale optimization algorithm,” Memories - Mater. Devices, Circuits Syst., vol. 6, no. October, p. 100086, 2023, doi: 10.1016/j.memori.2023.100086.
  25. J. F. Olesen and H. R. Shaker, “Predictive maintenance for pump systems and thermal power plants: State-of-the-art review, trends and challenges,” Sensors (Switzerland), vol. 20, no. 8, 2020, doi: 10.3390/s20082425.
Index Terms

Computer Science
Information Sciences


Humidity sensor NPK sensor Growth Watering