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An auto-validation method for a complete IoT pivot irrigation model based on the Penman–Monteith equation
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  • Published: 02 April 2026

An auto-validation method for a complete IoT pivot irrigation model based on the Penman–Monteith equation

  • Abdelrahman Osman Elfaki1,
  • Saleh Ali Albelwi1,
  • Abderrahim Lakhouit2,
  • Osama Moh’d Alia1,
  • Mohamed Elsawy2,
  • Anas Bushnag3,
  • Raghad Mahmoud Alqobali4,
  • Mohammed Alotaibi5,
  • Ashraf Marei3 &
  • …
  • Tareq Alhmiedat5,6 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Civil engineering
  • Environmental sciences
  • Hydrology

Abstract

Pivot irrigation has been introduced as an engineering solution to cultivate large areas of farmland without increasing water usage. Although research studies have proposed different types of pivot irrigation systems, several challenges must be addressed to create a successful system. These challenges include determining crop water requirements, IoT components and architecture, and compatibility, as well as data interpretation, environmental factors, scalability, and result validation. This paper provides an auto-validation method for a complete IoT pivot irrigation model based on the Penman–Monteith equation. Auto-validation is crucial to protecting the pivot system from sensor errors caused by telecom network interference or natural factors. Furthermore, the proposed model effectively addresses all the aforementioned challenges, making it the first comprehensive IoT solution. This paper also develops a benchmark framework for evaluating pivot irrigation systems, providing a standardized basis for performance assessment in future research. As an initial experimental study, the evaluation was conducted using a single crop type (grass) at one field site over a period of 49 days, representing a proof-of-concept validation. Real-world experiments were performed to assess the accuracy and applicability of the proposed model. The results demonstrate significant improvements over traditional irrigation methods, highlighting the system’s effectiveness in optimizing water usage and enhancing agricultural productivity.

Data availability

The dataset supporting the findings of this study has been made publicly available on Kaggle and can be accessed at: https://www.kaggle.com/datasets/tareqalhmiedat/sensor-dataset-for-the-penmanmonteith-equation.

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Acknowledgements

The authors extend their appreciation to the Deanship of Research and Graduate Studies at the University of Tabuk for funding this work through Research No. 0113-1444-S.

Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia

    Abdelrahman Osman Elfaki, Saleh Ali Albelwi & Osama Moh’d Alia

  2. Department of Civil Engineering, Faculty of Engineering, Geotechnical and Foundations Engineering at University of Tabuk, 71491, Tabuk, Saudi Arabia

    Abderrahim Lakhouit & Mohamed Elsawy

  3. Department of Computer Engineering, Faculty of Computers and Information Technology, University of Tabuk, 71491, Tabuk, Saudi Arabia

    Anas Bushnag & Ashraf Marei

  4. National Center for Artificial Intelligence (NCAI), Riyadh, Saudi Arabia

    Raghad Mahmoud Alqobali

  5. Department of Information Technology, Faculty of Computers and Information Technology, University of Tabuk, 71491, Tabuk, Saudi Arabia

    Mohammed Alotaibi & Tareq Alhmiedat

  6. Artificial Intelligence and Sensing Technologies (AIST) Research Center, University of Tabuk, 71491, Tabuk, Saudi Arabia

    Tareq Alhmiedat

Authors
  1. Abdelrahman Osman Elfaki
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  2. Saleh Ali Albelwi
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  3. Abderrahim Lakhouit
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  4. Osama Moh’d Alia
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  5. Mohamed Elsawy
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  6. Anas Bushnag
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  7. Raghad Mahmoud Alqobali
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  8. Mohammed Alotaibi
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  9. Ashraf Marei
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  10. Tareq Alhmiedat
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Contributions

A.O.E., S.E., and T.E. developed the conceptualization and methodology, and wrote the main text, and A.L., O.M.A., M.E., A.B conduct the experiments and developed the software, R.M.A, M.A., A.M. validate the experiments and results. All authors reviewed the manuscript.

Corresponding author

Correspondence to Abdelrahman Osman Elfaki.

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The authors declare no competing interests.

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Cite this article

Elfaki, A.O., Albelwi, S.A., Lakhouit, A. et al. An auto-validation method for a complete IoT pivot irrigation model based on the Penman–Monteith equation. Sci Rep (2026). https://doi.org/10.1038/s41598-026-46804-3

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  • Received: 19 March 2025

  • Accepted: 27 March 2026

  • Published: 02 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-46804-3

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Keywords

  • Crop water requirements
  • Irrigation system scalability
  • IoT
  • Penman–Monteith equation
  • Pivot irrigation
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