Design and Implementation of an Iot-Based Smart Irrigation System for Real-Time Monitoring, Remote Control, and Optimized Water Usage in Precision Agriculture
Authors
Department of Electrical Engineering, Bayero University, Kano, Nigeria (Nigeria)
Department of Electrical Engineering, Aliko Dangote University of Science and Technology, Wudil, Kano, Nigeria (Nigeria)
Department of Electrical and Electronics Engineering, Federal Polytechnic Daura, Katsina, Nigeria (Nigeria)
Article Information
DOI: 10.51584/IJRIAS.2026.11030081
Subject Category: Agriculture
Volume/Issue: 11/3 | Page No: 1037-1046
Publication Timeline
Submitted: 2026-03-21
Accepted: 2026-03-26
Published: 2026-04-13
Abstract
The escalating global demand for water conservation, coupled with the need for sustainable and efficient agricultural practices, has accelerated the development of smart irrigation systems based on the Internet of Things (IoT). However, despite significant progress, existing systems largely rely on threshold-based control using soil moisture data, with limited integration of advanced artificial intelligence (AI)-driven predictive models that incorporate multi-source inputs such as weather forecasts, evapotranspiration rates, and crop-specific water requirements. This limitation reduces the overall efficiency and adaptability of irrigation systems under dynamic environmental conditions. In response, this study presents the design and implementation of an IoT-based smart irrigation system that integrates real-time sensing, remote monitoring, and automated control to optimize water usage and enhance crop productivity. The proposed system combines soil moisture sensing, environmental monitoring, and cloud-based data processing to enable intelligent, data-driven irrigation scheduling. A key contribution of this work is the development of a data-driven decision-making framework that improves irrigation efficiency beyond conventional manual and threshold-based approaches. The research further examines core system components, including IoT-enabled sensor networks, meteorological monitoring devices, and AI-based predictive analytics, while reviewing diverse architectures such as Arduino-based microcontroller platforms, wireless sensor networks, and cloud computing infrastructures. Empirical evaluations demonstrate that the proposed system achieves significant reductions in water wastage while improving crop yields through precise irrigation control. Overall, this study provides a comprehensive and scalable system architecture that integrates hardware, communication networks, and cloud platforms, offering a practical solution for precision agriculture. It also highlights the potential for incorporating advanced AI models and secure communication mechanisms, such as blockchain, to enhance system reliability, scalability, and cybersecurity in future smart irrigation applications.
Keywords
IOT, Arduino, Proteus, LED & LCD, Sensor, GSM (SIM800L, SIM900A), AI.
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References
1. Patel, H., et al. (2022). GSM Modem-Based IoT System for Remote Monitoring and Control. Journal of Engineering Research and Applications, 12(2), 28-36. [Google Scholar] [Crossref]
2. Patel, H., et al. (2022). Challenges and Opportunities in IoT-Based Smart Irrigation Systems. Journal of Engineering Research and Applications, 12(2), 19-27. [Google Scholar] [Crossref]
3. Jha, S., et al. (2022). Smart Irrigation System Using Soil Moisture Sensor, Ultrasonic Sensor, and Relay Module. Journal of Precision Agriculture, 23(1), 147-159. [Google Scholar] [Crossref]
4. Singh, S., et al. (2021). Smart Irrigation Systems: A Review. Journal of Agricultural Engineering Research, 63, 100940. [Google Scholar] [Crossref]
5. Chalvantharan A, Lim CH, Ng DKS. Economic feasibility and water footprint analysis for smart irrigation systems in the palm oil industry. Sustainability. 2023;15(10):8069. doi: 10.3390/su15108069. [Google Scholar] [Crossref]
6. Kavyashree T, Shreedhara KS. Intelligent IoT-based smart irrigation system. Int J Creat Res Thoughts. 2021;9(2):2709–22. [Google Scholar] [Crossref]
7. Birner, R. & Anderson, J.R. (2021). Agricultural development and economic growth. In agricultural development and economic transformation (pp. 11-34). Palgrave Macmillan. [Google Scholar] [Crossref]
8. Monhanty, S. P., et al. (2019). Smart farming using IoT and machine learning. IEEE transactions on industrial informations 15(4), 1884-1892. [Google Scholar] [Crossref]
9. Smith J. 13 June 2022"Overload relay - Principle of operation, types, connection". www.electricalclassroom.com. 2020-02-15. Retrieved 2022-06-13.) [Google Scholar] [Crossref]
10. Kumar, J.P. et al. (2014). Implementing Intelligent Monitoring Techniques in Agriculture Using Wireless Sensor Networks, International Journal of Computer Science and Information Technologies, 5 (4), 5797-5800. [Google Scholar] [Crossref]
11. Amritansh Singh, Tarun Sharma, Deepank Grover, Keshav Goel, Sujay Deb, "A Cortex M0 SoC-Based IoT Platform for Agricultural Applications", 2023 IEEE International Symposium on Smart Electronic Systems (iSES), pp.236-241, 2023. [Google Scholar] [Crossref]
12. Assessment of IOT for the Indian Agriculture Sector. In the 47th Mid-Term Symposium on Modern Information and Communication Technologies for Digital India, Chandigarh. [Google Scholar] [Crossref]
13. Comparison of Water Use Efficiency in Traditional and Modern Irrigation Systems" by Fernández, J. E., et al. (2022) [Google Scholar] [Crossref]
14. Rijnaarts, H. H. M., et al. (2023). Optimizing Water Usage in Agriculture using IoT-Based Smart Irrigation Systems. Journal of Cleaner Production, 392, 135671. [Google Scholar] [Crossref]
15. S. M. Čisar, P. S. Molcer, and R. Pinter, “Design and Implementation of an IoT-Based Smart Irrigation System for Sustainable Agriculture, ,” vol. 22, no. 12, pp. 315–328, 2025. [Google Scholar] [Crossref]
16. S. O. Ibharunujele, J. S. Mommoh, S. A. Shuaibu, and R. Chinyere, “Design and Implementation of an Intelligent IoT-Based Smart Irrigation System with Real-Time GSM Alerts for Efficient Water Management,” 2025. [Google Scholar] [Crossref]
17. G. Poojitha and M. Sravani, “Design and Implementation of an IoT-Based Smart Irrigation System for Agricultural Application, ” pp. 1–6. [Google Scholar] [Crossref]
18. J. Srikanthnaik, “Design and implementation of an IoT-based smart irrigation system for efficient water management and sustainable agriculture,” vol. 7, no. 1, pp. 459–465, 2024. [Google Scholar] [Crossref]
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