Development of an automated irrigation system based on artificial intelligence technology to support efficient and sustainable integrated agriculture
DOI:
https://doi.org/10.61511/stum.v1i2.2024.1266Keywords:
artificial intelligence, irrigation, agricultureAbstract
Background : The need to enhance agricultural productivity while ensuring sustainability in the modern era has become increasingly urgent. One of the challenges faced is inefficiency in irrigation, which can lead to water wastage, land degradation, and reduced agricultural productivity, thereby threatening the sustainability of this sector. This scientific paper aims to find a solution by developing an automated irrigation system based on artificial intelligence technology that can support and enhance efficiency and sustainability in integrated agriculture. Methods: Data collection for this paper employed documentary study techniques. The data used as supporting references were obtained from journals and other credible sources relevant to the discussed topic. Findings: Based on the results of the documentary study, AI technology can assist farmers in efficiently managing their land. With an automated irrigation system, farmers' tasks can be carried out more easily, and water resources are utilized only as needed. Furthermore, energy consumption is significantly reduced, leading to overall cost savings and high cost efficiency. Efficiency in irrigation and water management ensures that crops and harvests receive only the necessary amount of water, thereby minimizing waste caused by both water shortages and excesses. Conclusion: he implementation of an automated irrigation system based on artificial intelligence (AI) technology can enhance the efficiency and sustainability of integrated agriculture by adjusting water usage based on real-time weather data and soil conditions. However, several unresolved challenges remain in applying this technology. Novelty/Originality of this article: This article introduces an AI-based automated irrigation system designed for sustainable agriculture. It optimizes water use by leveraging real-time weather and soil data, thereby enhancing both productivity and sustainability. By addressing barriers to technology adoption, this study provides valuable insights for future research, demonstrating the economic viability and efficiency of AI-driven irrigation systems for farmers.
References
Angelin, B. J., & Kumar, A. (2021). Teknik sistem irigasi cerdas menggunakan kecerdasan buatan dan IoT. Prosiding Konferensi Internasional ke-3 tentang Teknologi Komunikasi Cerdas dan Jaringan Seluler Virtual, ICICV 2021, 1355–1359. https://doi.org/10.1109/ICICV50876.2021.9388444.
Anggraeni, N. M., Ayuningtiyas, L., Kinasih, E. R., Sudarti, Firdha, & Anggraeni, K. A. (2024). Analisis konsep penerapan mekanika dalam sistem irigasi pertanian berbasis teknologi. Optika: Jurnal Pendidikan Fisika, 8(2), 248–257. https://doi.org/10.37478/optika.v8i2.4222.
Cahyani, P. M. (2023). IoT dalam pertanian cerdas 4.0 untuk upaya meningkatkan efisiensi agribisnis. Jurnal Ilmu Teknologi Informasi dan Sains. https://www.researchgate.net/publication/369378549.
Cahyani, S. E., Rohana, T., & Lestari, S. A. P. (2023). Implementasi fuzzy logic pada sistem pengairan sawah dalam meningkatkan efisiensi penggunaan air berbasis IoT. INFOTECH: Jurnal Informatika dan Teknologi, 4(1), 37–46. https://doi.org/10.37373/infotech.v4i1.496.
Goap, A., Sharma, D., Shukla, A. K., & Rama Krishna, C. (2018). Sistem manajemen irigasi cerdas berbasis IoT menggunakan machine learning dan teknologi open source. Computers and Electronics in Agriculture, 155, 41–49. https://doi.org/10.1016/j.compag.2018.09.040.
Harahap, M. A. K., Suparwata, D. O., & Rijal, S. (2023). Penerapan irigasi terpadu untuk mengatasi musim kemarau dalam pertanian padi. Jurnal Geosains West Science, 1(03), 151–158. https://wnj.westscience-press.com/index.php/jgws/index.
Hasibuan, M. R. R. (2023). Evaluasi efisiensi penggunaan air dalam pertanian berbasis teknologi irigasi modern. Universitas Medan Area. https://doi.org/10.31219/osf.io/kcvfy.
Linaza, M. T., Posada, J., Bund, J., Eisert, P., Quartulli, M., Döllner, J., Pagani, A., Olaizola, I. G., Barriguinha, A., Moysiadis, T., & Lucat, L. (2021). Aplikasi kecerdasan buatan berbasis data untuk pertanian presisi berkelanjutan. Agronomy, 11(6), 1–14. https://doi.org/10.3390/agronomy11061227.
Maulana, A., & Sari, N. L. D. M. (2024). Tinjauan literatur implementasi kecerdasan buatan dalam pertanian. Seminar Nasional Informatika-FTI UPGRIS, 2, 512–530. https://conference.upgris.ac.id/index.php/infest/article/view/6479.
Obaideen, K., Yousef, B. A. A., AlMallahi, M. N., Tan, Y. C., Mahmoud, M., Jaber, H., & Ramadan, M. (2022). Tinjauan sistem irigasi cerdas menggunakan IoT. Energy Nexus, 7, 1–11. https://doi.org/10.1016/j.nexus.2022.100124.
Peñailillo, F. F., Gutter, K., Vega, R., & Silva, G. C. (2024). Teknologi transformatif dalam pertanian digital: memanfaatkan internet of things, penginderaan jauh, dan kecerdasan buatan untuk manajemen tanaman cerdas. Journal of Sensor and Actuator Networks, 13(4), 1–26. https://doi.org/10.3390/jsan13040039.
Raouhi, E. M., Zouizza, M., Lachgar, M., Zouani, Y., Hrimech, H., & Kartit, A. (2023). AIDSII: Sistem digital berbasis AI untuk irigasi cerdas. Software Impacts, 17, 1–3. https://doi.org/10.1016/j.simpa.2023.100574.
Shandilya, U., & Khanduja, V. (2020). Sistem pertanian cerdas dengan dukungan ramalan cuaca dan prediksi tanaman. Konferensi Internasional tentang Komputasi, Komunikasi, dan Keamanan (ICCCS), 1-6. https://ieeexplore.ieee.org/abstract/document/9277437.
Downloads
Published
Issue
Section
Citation Check
License
Copyright (c) 2025 Shefani Eka Putri, Fitriana Heni Tiali Susanti, Amanda Neswantari
This work is licensed under a Creative Commons Attribution 4.0 International License.
