Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization

Authors

DOI:

https://doi.org/10.24925/turjaf.v13i7.1720-1730.7524

Keywords:

collective irrigation, particle swarm optimization, smart irrigation, socio-economic contribution, water equitable distribution

Abstract

This article explores an intelligent and equitable approach to collective and participatory irrigation for small farmers, with an emphasis on the democratization of water use. It examines how this equitable irrigation approach can contribute to the social economy by improving irrigation efficiency and reducing costs for farmers. This work highlights the socio-economic benefits of this approach and highlights its potential to promote democratic water management particularly for small-scale farmers. To do this, we propose a collective irrigation system using a Particle Swarm Optimization (PSO) algorithm, to accurately estimate crop water needs, a method of equitable distribution of water according to needs. Additionally, we propose a novel weighted aggregation technique to establish irrigation priorities among crops, taking into account factors such as crop yield, water scarcity, and economic value.

References

Asma’ Tajul Arifin, Nur Aishah Arshad, & Aishath Muneeza. (2018). The Application of Blockchain Technology in Crowdfunding: Towards Financial Inclusion via Technology. International Journal of Management and Applied Research, 2, 82–98.

Barbara Rose Johnston. (2012). Water, Cultural Diversity, and Global Environmental Change: Emerging Trends, Sustainable Futures? (Lisa Hiwasaki, Irene J. Klaver, Ameyali Ramos Castillo, & Veronica Strang, Eds.). Springer.

Basso, B., & Antle, J. (2020). Digital agriculture to design sustainable agricultural systems. Nature Sustainability, 3(4), 254–256. https://doi.org/10.1038/s41893-020-0510-0

Beaulieu, T., Sarker, S., & Sarker, S. (2015). A Conceptual Framework for Understanding Crowdfunding. Communications of the Association for Information Systems, 37. https://doi.org/10.17705/1CAIS.03701

Benzaouia, M., Hajji, B., Mellit, A., & Rabhi, A. (2023). Fuzzy-IoT smart irrigation system for precision scheduling and monitoring. Computers and Electronics in Agriculture, 215, 108407. https://doi.org/10.1016/J.COMPAG.2023.108407

David Molden. (2013). Water for Food Water for Life (D. Molden, Ed.; 1st ed.). Routledge. https://doi.org/10.4324/9781849773799

Et-taibi, B., Abid, M. R., Boufounas, E. M., Morchid, A., Bourhnane, S., Abu Hamed, T., & Benhaddou, D. (2024). Enhancing water management in smart agriculture: A cloud and IoT-Based smart irrigation system. Results in Engineering, 22. https://doi.org/10.1016/j.rineng.2024.102283

Gonzalez Perea, R., Ballesteros, R., Ortega, J. F., & Moreno, M. Á. (2021). Water and energy demand forecasting in large-scale water distribution networks for irrigation using open data and machine learning algorithms. Computers and Electronics in Agriculture, 188, 106327. https://doi.org/10.1016/j.compag.2021.106327

Ibrahim Mohammad Abuzanouneh, K., N. Al-Wesabi, F., Abdulrahman Albraikan, A., Al Duhayyim, M., Al-Shabi, M., Mustafa Hilal, A., Ahmed Hamza, M., Sarwar Zamani, A., & Muthulakshmi, K. (2022). Design of Machine Learning Based Smart Irrigation System for Precision Agriculture. Computers, Materials & Continua, 72(1), 109–124. https://doi.org/10.32604/cmc.2022.022648

Ikidid, A., Fazziki, A. El, & Sadgal, M. (2021). Smart Collective Irrigation: Agent and Internet of Things based system. Proceedings of the 13th International Conference on Management of Digital EcoSystems, 100–106. https://doi.org/10.1145/3444757.3485113

Jain, M., Saihjpal, V., Singh, N., & Singh, S. B. (2022). An Overview of Variants and Advancements of PSO Algorithm. Applied Sciences, 12(17), 8392. https://doi.org/10.3390/app12178392

Khatoon, Z., Huang, S., Rafique, M., Fakhar, A., Kamran, M. A., & Santoyo, G. (2020). Unlocking the potential of plant growth-promoting rhizobacteria on soil health and the sustainability of agricultural systems. Journal of Environmental Management, 273, 111118. https://doi.org/10.1016/j.jenvman.2020.111118

Klerkx, L., & Begemann, S. (2020). Supporting food systems transformation: The what, why, who, where and how of mission-oriented agricultural innovation systems. Agricultural Systems, 184, 102901. https://doi.org/10.1016/j.agsy.2020.102901

Koech, R., & Langat, P. (2018). Improving Irrigation Water Use Efficiency: A Review of Advances, Challenges and Opportunities in the Australian Context. Water, 10(12), 1771. https://doi.org/10.3390/w10121771

Levidow, L., Zaccaria, D., Maia, R., Vivas, E., Todorovic, M., & Scardigno, A. (2014). Improving water-efficient irrigation: Prospects and difficulties of innovative practices. Agricultural Water Management, 146, 84–94. https://doi.org/10.1016/j.agwat.2014.07.012

Masood Ahmed, & Eduardo Araral. (2019). Water Governance in India: Evidence on Water Law, Policy, and Administration from Eight Indian States. Water, 11(10), 2071. https://doi.org/10.3390/w11102071

Matos, F., & Dias, R. (2023). Water governance as an instrument of democratization: reflections on the shared management of water resources in Brazil. In DEVELOPMENT AND ITS APPLICATIONS IN SCIENTIFIC KNOWLEDGE. Seven Editora. https://doi.org/10.56238/devopinterscie-047

Morchid, A., Et-taibi, B., Oughannou, Z., Alami, R. El, Qjidaa, H., Jamil, M. O., Boufounas, E. M., & Abid, M. R. (2025). IoT-enabled smart agriculture for improving water management: A smart irrigation control using embedded systems and Server-Sent Events. Scientific African, 27. https://doi.org/10.1016/j.sciaf.2024.e02527

Obaideen, K., Yousef, B. A. A., AlMallahi, M. N., Tan, Y. C., Mahmoud, M., Jaber, H., & Ramadan, M. (2022). An overview of smart irrigation systems using IoT. Energy Nexus, 7, 100124. https://doi.org/10.1016/j.nexus.2022.100124

Peter Baeck, & Liam Collins. (2015, July 8). Crowdfunding public services-tapping into the crowd to finance public projects. Nesta.

Rehman, A. U., Alamoudi, Y., Khalid, H. M., Morchid, A., Muyeen, S. M., & Abdelaziz, A. Y. (2024). Smart agriculture technology: An integrated framework of renewable energy resources, IoT-based energy management, and precision robotics. Cleaner Energy Systems, 9. https://doi.org/10.1016/j.cles.2024.100132

Saad, A., Benyamina, A. E. H., & Gamatie, A. (2020). Water Management in Agriculture: A Survey on Current Challenges and Technological Solutions. IEEE Access, 8, 38082–38097. https://doi.org/10.1109/ACCESS.2020.2974977

Saiti, B., Afghan, M., & Noordin, N. H. (2018). Financing agricultural activities in Afghanistan: a proposed salam -based crowdfunding structure. ISRA International Journal of Islamic Finance, 10(1), 52–61. https://doi.org/10.1108/IJIF-09-2017-0029

Sanchis-Ibor, C., Molle, F., & Kuper, M. (2020). Irrigation and water governance. In Water Resources in the Mediterranean Region (pp. 77–106). Elsevier. https://doi.org/10.1016/B978-0-12-818086-0.00004-2

Tambi, M. F. (2022). Understanding the Potentials and Challenges of Agricultural Technology Based Crowdfunding in Malaysia. Social & Management Research Journal, 19(1), 89–106. https://doi.org/10.24191/smrj.v19i1.17247

Thomas Bartz-Beielstein, Konstantinos Parsopoulos, & Michael N. Vrahatis. (2002). Tuning PSO parameters through sensitivity analysis. Interner Bericht Des Sonderforschungsbereichs (SFB) 531 Computational Intelligence No.CI-124/02.

Torres-Sanchez, R., Navarro-Hellin, H., Guillamon-Frutos, A., San-Segundo, R., Ruiz-Abellón, M. C., & Domingo-Miguel, R. (2020). A Decision Support System for Irrigation Management: Analysis and Implementation of Different Learning Techniques. Water, 12(2), 548. https://doi.org/10.3390/w12020548

Wei, S., Xu, T., Niu, G.-Y., & Zeng, R. (2022). Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains. Remote Sensing, 14(13), 3004. https://doi.org/10.3390/rs14133004

Zhu, H., & Zhou, Z. Z. (2016). Analysis and outlook of applications of blockchain technology to equity crowdfunding in China. Financial Innovation, 2(1), 29. https://doi.org/10.1186/s40854-016-0044-7

Zinkernagel, J., Maestre-Valero, Jose. F., Seresti, S. Y., & Intrigliolo, D. S. (2020). New technologies and practical approaches to improve irrigation management of open field vegetable crops. Agricultural Water Management, 242, 106404. https://doi.org/10.1016/j.agwat.2020.106404

Downloads

Published

30.07.2025

Issue

Section

Research Paper