Research Article

Cloud Computing Based Smart Irrigation System for Big Farms

Volume: 8 Number: 2 December 22, 2024
EN

Cloud Computing Based Smart Irrigation System for Big Farms

Abstract

The main purpose of this study is to determine the optimum consumption of water and the required water consumption in agricultural irrigation systems. A smart irrigation system includes utilizing innovation to optimize and computerize the watering of plants. It regularly utilizes sensors, climate information, and mechanization frameworks to convey the proper amount of water at the correct time, making strides effectiveness and moderating assets. The increase in water needs compared to the increase in population growth requires management of water sources and saving consumption. With progression in innovated technologies, we will set up a system that controlled the irrigation such that there's productive usage of water and make an ease of work for the farmers. By using internet of things and embedded technology, a cloud based smart irrigation system have been implemented in this work. In this system, the required amount of water is accurately supplied to the plants by obtaining the required information regarding moisture of soil, temperature levels and changes in lighting intensity, which is provided via sensors. These sensors are connected through peripheral devices deployed in the work field to collect information about the weather and soil condition and send this data to the nearest wireless server that will store it on the cloud. Field workers will be able to monitor changes in parameters through dashboards on a website integrated with cloud storage. IoT utilization enables the workers in the field to make an estimation of the required amount of water within the upcoming days. These technological means enable us to study, compare and analyze data for different times during the year and find different ways to reduce and conserve water consumption.

Keywords

References

  1. [1] García, I.F., Montesinos, P., Poyato, E.C., and Díaz, J.R.,, "Optimal design of pressurized irrigation networks to minimize the operational cost under different management scenarios," Water resources management, p. 31(6), 1995.
  2. [2] G. M. P. P. M. a. L. D. Cáceres, "Smart Farm Irrigation Model Predictive Control for Economic Optimal Irrigation," Agriculture, Agronomy, vol. 11, no. 9, p. 1810, 2021.
  3. [3] J. O.-M. J. G. J. a. C. J. Domínguez-Niño, "Differential irrigation scheduling by an automated algorithm of water balance tuned by capacitance-type soil moisture sensors," Agricultural Water Management, vol. 228, no. 105880, 2020.
  4. [4] A. H. N. a. R. S. McCarthy, "Advanced process control of irrigation," the current state and an analysis to aid future development, Irrigation Science, vol. 31(3), pp. 183 - 192, 2013.
  5. [5] J. M. M. M. J. a. G. J. Casadesús, "A general algorithm for automated scheduling of drip irrigation in tree crops,," Computers and Electronics in Agriculture, vol. 83, pp. 11-20, 2012.
  6. [6] R. P. E. a. D. J. Perea, "Forecasting of applied irrigation depths at farm level for energy tariff periods using Coactive neuro-genetic fuzzy system," Agricultural Water Management, no. 107068., p. 256, 2021.
  7. [7] A. R. a. J. P. M. Bhattacharya, "Smart Irrigation System Using Internet of Things," Applications of Internet of Things, pp. 119-129, 2021.
  8. [8] A. S. Chandra Prakash Meher, "IoT based Irrigation and Water Logging monitoring system using Arduino and Cloud Computing," in International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), 2019.

Details

Primary Language

English

Subjects

Networking and Communications, Cloud Computing

Journal Section

Research Article

Authors

Laith Ali Abdul Rahim This is me
Iraq

Early Pub Date

December 17, 2024

Publication Date

December 22, 2024

Submission Date

November 6, 2024

Acceptance Date

December 16, 2024

Published in Issue

Year 2024 Volume: 8 Number: 2

APA
A. Kamel, H., & Abdul Rahim, L. A. (2024). Cloud Computing Based Smart Irrigation System for Big Farms. International Journal of Multidisciplinary Studies and Innovative Technologies, 8(2), 127-132. https://izlik.org/JA65JT96EG
AMA
1.A. Kamel H, Abdul Rahim LA. Cloud Computing Based Smart Irrigation System for Big Farms. IJMSIT. 2024;8(2):127-132. https://izlik.org/JA65JT96EG
Chicago
A. Kamel, Haider, and Laith Ali Abdul Rahim. 2024. “Cloud Computing Based Smart Irrigation System for Big Farms”. International Journal of Multidisciplinary Studies and Innovative Technologies 8 (2): 127-32. https://izlik.org/JA65JT96EG.
EndNote
A. Kamel H, Abdul Rahim LA (December 1, 2024) Cloud Computing Based Smart Irrigation System for Big Farms. International Journal of Multidisciplinary Studies and Innovative Technologies 8 2 127–132.
IEEE
[1]H. A. Kamel and L. A. Abdul Rahim, “Cloud Computing Based Smart Irrigation System for Big Farms”, IJMSIT, vol. 8, no. 2, pp. 127–132, Dec. 2024, [Online]. Available: https://izlik.org/JA65JT96EG
ISNAD
A. Kamel, Haider - Abdul Rahim, Laith Ali. “Cloud Computing Based Smart Irrigation System for Big Farms”. International Journal of Multidisciplinary Studies and Innovative Technologies 8/2 (December 1, 2024): 127-132. https://izlik.org/JA65JT96EG.
JAMA
1.A. Kamel H, Abdul Rahim LA. Cloud Computing Based Smart Irrigation System for Big Farms. IJMSIT. 2024;8:127–132.
MLA
A. Kamel, Haider, and Laith Ali Abdul Rahim. “Cloud Computing Based Smart Irrigation System for Big Farms”. International Journal of Multidisciplinary Studies and Innovative Technologies, vol. 8, no. 2, Dec. 2024, pp. 127-32, https://izlik.org/JA65JT96EG.
Vancouver
1.Haider A. Kamel, Laith Ali Abdul Rahim. Cloud Computing Based Smart Irrigation System for Big Farms. IJMSIT [Internet]. 2024 Dec. 1;8(2):127-32. Available from: https://izlik.org/JA65JT96EG