Applied Agriculture Sciences
Agriculture and food sciences | Online ISSN: 3066-3407
  1. You are here:
  2. Home
  3. Journals
  4. Food & Agriculture
Applied Agriculture Sciences

Volume 3 Number 1 2025

Article Contents

REVIEWS   (Open Access)
Contents Vol 3 (1)

AI-Driven Microgrid Solutions for Enhancing Irrigation Efficiency in Rural Farming

Ashok Kumar Chowdhury1*, Md. Sakib Mahdi Aziz2

+ Author Affiliations

Applied Agriculture Sciences 3 (1) 1-6 https://doi.org/10.25163/agriculture.3110299

Submitted: 08 April 2025 Revised: 11 June 2025  Published: 12 June 2025 

Abstract

The fresh water we draw off from lakes and rivers goes to farm fields about 70%, and antiquated flooding techniques waste tons of that lifeblood while consuming through electricity. In many remote villages control is intermittent, so farmers are often left cycling on loud, diesel generators that subsidize the air and extract money from their wallets. A new type of off-grid, AI-driven technology now weans together small solar panels or small wind turbines with smart controllers that adjust water resources to real demand. Pulling composed real-time delivers from soil probes, forecasts, well spectacles, old moisture logs, crop models, and machine-learning nudges, the system chooses on the advertisement when to exposed the valves, how many loads to send, and how much control the motors should attraction. In trials that trim lachrymation by 20-40 % chop vigor costs by unevenly forty percent, and lift produces by fifteen to thirty percent, farmers devote less and take homebased more. Swapping diesel rigs for these tiny microgrids also trims on-farm greenhouse gases by roughly 35% percent, giving each grower a real stake in the climate fight. This review pulls together what we know about the technology itself, its social and economic effects, the hurdles it faces, and the paths forward for AI-powered microgrid irrigation. By using water and power more wisely, these tools could reshape farming, uplift rural communities, and bolster global food security and environmental health where every drop and watt counts.

Keywords: AI-driven microgrid, irrigation efficiency, rural farming, precision irrigation, renewable energy

References

Arévalo, P., Ochoa-Correa, D., & Villa-Ávila, E. (2024). Optimizing microgrid operation: integration of emerging technologies and artificial intelligence for energy efficiency. Electronics, 13(18), 3754. https://doi.org/10.3390/electronics13183754

Abdullah, M. S., Tasnim, K., Karim, M. Z., & Hasan, R. (2025). Improving Market Competitiveness using the Use of Artificial Intelligence in Strategic Business Decisions. Business & Social Sciences, 3(1), 1-9.

Abioye, E. A., Hensel, O., Esau, T. J., Elijah, O., Abidin, M. S. Z., Ayobami, A. S., Yerima, O., & Nasirahmadi, A. (2022). Precision irrigation management using machine learning and digital farming solutions. AgriEngineering, 4(1), 70–103. https://doi.org/10.3390/agriengineering4010006

Ali, A. O., Elmarghany, M. R., Abdelsalam, M. M., Sabry, M. N., & Hamed, A. M. (2022). Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review. Journal of Energy Storage, 50, 104609. https://doi.org/10.1016/j.est.2022.104609

Ashoka, P., Devi, B. R., Sharma, N., Behera, M., Gautam, A., Jha, A., & Sinha, G. (2024). Artificial Intelligence in Water Management for Sustainable Farming: A Review. Journal of Scientific Research and Reports, 30(6), 511-525.

Akanbi, M. B., Banjoko, I. K., Adedotun, K. J., & Raji, A. K. (2024, October 31). AI-POWERED SMART IRRIGATION SYSTEMS AND SOLAR ENERGY INTEGRATION: a SUSTAINABLE APPROACH TO ENHANCING AGRICULTURAL PRODUCTIVITY IN NIGERIA. https://ssaapublications.com/index.php/sjratr/article/view/330

Bwambale, E., Abagale, F. K., & Anornu, G. K. (2021). Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review. Agricultural Water Management, 260, 107324. https://doi.org/10.1016/j.agwat.2021.107324

Candelise, C., Winskel, M., & Gross, R. J. (2013). The dynamics of solar PV costs and prices as a challenge for technology forecasting. Renewable and Sustainable Energy Reviews, 26, 96–107. https://doi.org/10.1016/j.rser.2013.05.012

Dhillon, R., & Moncur, Q. (2023). Small-Scale Farming: A review of challenges and potential opportunities offered by technological advancements. Sustainability, 15(21), 15478. https://doi.org/10.3390/su152115478

Elmahdi, A. (2024). Addressing water scarcity in agricultural irrigation: By exploring alternative water resources for sustainable irrigated agriculture. Irrigation and Drainage. https://doi.org/10.1002/ird.2973

Enahoro-Ofagbe, F. E., Ewansiha, S., & Iwuozor, K. O. (2024). Integrating irrigation management and soil remediation practices for sustainable agricultural production: advances, challenges, and future directions. Agroecology and Sustainable Food Systems, 1–27. https://doi.org/10.1080/21683565.2024.2427784

Falcone, P. M. (2023). Sustainable Energy Policies in Developing Countries: A Review of Challenges and opportunities. Energies, 16(18), 6682. https://doi.org/10.3390/en16186682

G, W. V. A. (2023b, September 1). Bringing the Water-Efficiency benefits of precision irrigation to Resource-Constrained farms through an Automatic Scheduling-Manual Operation irrigation tool. https://dspace.mit.edu/handle/1721.1/152638

Harnessing AI for Small-Scale Irrigation Systems: A Comprehensive Literature Review. (2024, November 4). IEEE Conference Publication | IEEE Xplore. https://ieeexplore.ieee.org/abstract/document/10796721

Hasan, R., Tasnim, K., Karim, M. Z., & Abdullah, M. S. (2024). Transforming the Digital Landscape: Analyzing the Role of Artificial Intelligence in Contemporary Marketing Strategies. Business & Social Sciences, 2(1), 1-10.

Hammouch, H. (2025, February 24). Application of advanced Artificial Intelligence models to manage irrigation using sensor data and satellite images. https://hal.science/tel-05089099/

Khan, M. R., Haider, Z. M., Malik, F. H., Almasoudi, F. M., Alatawi, K. S. S., & Bhutta, M. S. (2024). A comprehensive review of microgrid energy management strategies considering electric vehicles, energy storage systems, and AI techniques. Processes, 12(2), 270. https://doi.org/10.3390/pr12020270

Karim, M. Z., Hasan, R., Abdullah, M. S., & Tasnim, K. (2023). AIs Exceptional Potential to Significantly Improve the Profitability of Social Media Influencer Marketing. Business & Social Sciences, 1(1), 1-8.

Majeed, Y., Khan, M. U., Waseem, M., Zahid, U., Mahmood, F., Majeed, F., Sultan, M., & Raza, A. (2023). Renewable energy as an alternative source for energy management in agriculture. Energy Reports, 10, 344–359. https://doi.org/10.1016/j.egyr.2023.06.032

Muscettola, N., Nayak, P., Pell, B., & Williams, B. C. (1998). Remote Agent: to boldly go where no AI system has gone before. Artificial Intelligence, 103(1–2), 5–47. https://doi.org/10.1016/s0004-3702(98)00068-x

Mimmo, S. S., Roy, A., & Billal, S. A. (2025). Integrating Artificial Intelligence Across the Fashion Value AI Transforming Design, Production, and Consumer Experience. Applied IT & Engineering, 3(1), 1-10.

Namara, R. E., Hanjra, M. A., Castillo, G. E., Ravnborg, H. M., Smith, L., & Van Koppen, B. (2009). Agricultural water management and poverty linkages. Agricultural Water Management, 97(4), 520–527. https://doi.org/10.1016/j.agwat.2009.05.007

Rojas, L., Peña, Á., & Garcia, J. (2025). AI-Driven Predictive Maintenance in Mining: A systematic literature review on fault detection, digital twins, and intelligent asset management. Applied Sciences, 15(6), 3337. https://doi.org/10.3390/app15063337

Roy, A., & Ahmed, M. J. (2025). Tech-Driven Fashion Navigating the Opportunities and Challenges of Digitalization. Applied IT & Engineering, 3(1), 1-10.

Rutibabara, J. B. (2018, September 1). Environmental and Economic Cost Analysis of a Solar PV, Diesel and  hybrid PV-Diesel water Pumping Systems for Agricultural Irrigation in  Rwanda: Case study of Bugesera district. https://repository.pauwes-cop.net/handle/1/241

Roy, A. (2024). Artificial Intelligence in Advanced Manufacturing: Opportunities, Applications, and Challenges in the Context of Bangladesh. Applied IT & Engineering, 2(1), 1-8.

Rehman, A. U., Alamoudi, Y., Khalid, H. M., Morchid, A., Muyeen, S., & Abdelaziz, A. Y. (2024b). Smart Agriculture Technology: an integrated framework of renewable energy resources, IoT-Based energy management, and precision robotics. Cleaner Energy Systems, 9, 100132. https://doi.org/10.1016/j.cles.2024.100132

Roy, A. (2024). Fashion Innovation Driven by AI: Transforming Design, Manufacturing, and Customer Experience. Applied IT & Engineering, 2(1), 1-8.

Shareef, A. M. A., Seçkiner, S., Eid, B., & Abumeteir, H. (2024). Integration of blockchain with artificial intelligence technologies in the energy sector: a systematic review. Frontiers in Energy Research, 12. https://doi.org/10.3389/fenrg.2024.1377950

Shoeb, M., & Zillul, M. (2025). Artificial Intelligence in Digital Marketing Enhancing Personalization and Consumer Engagement. Business & Social Sciences, 3(1), 1-9.

Sadat, K. M., & Roy, A. (2025). Autonomous Systems Engineering: The Intersection of Robotics and AI. Applied IT & Engineering, 3(1), 1-8.

Sabir, R. M., Sarwar, A., Shoaib, M., Saleem, A., Alhousain, M. H., Wajid, S. A., Rasul, F., Shahid, M. A., Anjum, L., Safdar, M., Muhammad, N. E., Waqas, R. M., Zafar, U., & Raza, A. (2024). Managing water resources for sustainable agricultural production. In World sustainability series (pp. 47–74). https://doi.org/10.1007/978-3-031-63430-7_3

Tasnim, K., Abdullah, M. S., Karim, M. Z., & Hasan, R. (2025). AI-Driven Innovation, Privacy Issues, and Gaining Consumer Trust: The Future of Digital Marketing. Business & Social Sciences, 3(1), 1-7.

Ukoba, K., Olatunji, K. O., Adeoye, E., Jen, T., & Madyira, D. M. (2024). Optimizing renewable energy systems through artificial intelligence: Review and future prospects. Energy & Environment, 35(7), 3833–3879. https://doi.org/10.1177/0958305x241256293

Yakub, A. O., Adesanya, M. A., Same, N. N., Rabiu, A., Chaulagain, D., Ogunlowo, Q. O., Owolabi, A. B., Park, J., Lim, J., Lee, H., & Huh, J. (2024). Enhancing sustainable and climate-resilient agriculture: Optimization of greenhouse energy consumption through microgrid systems utilizing advanced meta-heuristic algorithms. Energy Strategy Reviews, 54, 101440. https://doi.org/10.1016/j.esr.2024.101440

Zillul, M., & Shoeb, M. (2025). Digital Marketing and Artificial Intelligence in Healthcare: Revolutionizing Patient Engagement and Service Delivery. Journal of Primeasia, 6(1), 1-10.


View Dimensions


View Plumx


View Altmetric



0
Save
0
Citation
105
View
0
Share