Energy Consumption Monitoring and Anomaly Detection Module for a Smart Automatic Irrigation System

Authors

DOI:

https://doi.org/10.18372/1990-5548.88.20975

Keywords:

smart irrigation, energy consumption monitoring, anomaly detection, IoT, energy efficiency, smart farming, automated control

Abstract

Modern smart automatic irrigation systems are widely used to improve water efficiency and crop productivity. However, most existing solutions primarily focus on soil moisture control and environmental conditions, while energy consumption behavior of irrigation equipment remains insufficiently analyzed. At the same time, abnormal energy consumption often serves as an early indicator of system malfunctions, water leakage, or inefficient operation of electromechanical components. This paper presents a module for monitoring energy consumption and detecting anomalies in a smart automatic irrigation system. The proposed solution is based on continuous measurement of electrical parameters and adaptive analysis of energy consumption patterns. The module enables early detection of abnormal operating conditions, improves energy efficiency, increases system reliability, and enhances operational autonomy. The developed approach can be integrated into existing irrigation infrastructures without significant hardware modifications and is suitable for private households and scalable smart farming systems.

 

Author Biographies

Mykola Vasylenko , State University “Kyiv Aviation Institute”

Candidate of Science (Engineering)

Associate Professor

Department of Avionics and Control Systems 

Olena Zahorna , DXC Consulting & Engineering Services POWERED BY AI, Kyiv

Senior Test Engineer

 

References

ESP32-S3-DevKitC-1 – ESP32-S3 – esp-dev-kits latest documentation. Technical Documents | Espressif Systems. URL: https://docs.espressif.com/projects/esp-dev-kits/en/latest/esp32s3/esp32-s3-devkitc-1/index.html (date of access: 03.10.2025).

Frontiers | Cloud–edge–device collaborative computing in smart agriculture: architectures, applications, and future perspectives / P. Yu et al. Frontiers. URL: https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2025.1668545/full?utm_source=chatgpt.com#B82 (date of access: 17.09.2025).

GeeksforGeeks. Anomaly detection techniques for large datasets – geeksforgeeks. GeeksforGeeks. URL: https://www.geeksforgeeks.org/blogs/anomaly-detection-techniques/ (date of access: 30.09.2025).

H. Bach and W. Mauser, Sustainable agriculture and smart farming,’’ in Earth Observation Open Science and Innovation. Cham, Switzerland: Springer, 2018, pp. 261–269. https://doi.org/10.1007/978-3-319-65633-5_12

K. R. Mukhamedova, N. P. Cherepkova, A. V. Korotkov, Z. B. Dagasheva, and M. Tvaronaviciene, ‘‘Digitalisation of agricultural production for precision farming: A case study,’’ Sustainability, vol. 14, no. 22, p. 14802, Nov. 2022. https://doi.org/10.3390/su142214802

M. Raj, S. Gupta, V. Chamola, A. Elhence, T. Garg, M. Atiquzzaman, and D. Niyato, ‘‘A survey on the role of Internet of Things for adopting and promoting agriculture 4.0,’’ J. Netw. Comput. Appl., vol. 187, Aug. 2021, Art. no. 103107. https://doi.org/10.1016/j.jnca.2021.103107

R. Akhter and S. A. Sofi, ‘‘Precision agriculture using IoT data analytics and machine learning,’’ J. King Saud Univ.-Comput. Inf. Sci., vol. 34, no. 8, pp. 5602–5618, Sep. 2022. https://doi.org/10.1016/j.jksuci.2021.05.013

Power monitoring and control systems. Monolithic Power Systems. URL: https://www.monolithicpower.com/en/learning/mpscholar/ac-power/power-conditioning-systems/power-monitoring-and-control-systems?srsltid=AfmBOorvzR9WaukXksW469_NrmjD2j6KMjy3eqsJv3Ba83mqwi4PBlhQ (date of access: 25.09.2025).

T. N. Gia, L. Qingqing, J. P. Queralta, Z. Zou, H. Tenhunen, and T. Westerlund, ‘‘Edge AI in smart farming IoT: CNNs at the edge and fog computing with LoRa,’’ in Proc. IEEE AFRICON, May 2019, pp. 1–6. https://doi.org/10.1109/AFRICON46755.2019.9134049

The role of smart irrigation systems in water conservation. Simple Green Energy. URL: https://www.simplegreenenergy.org/the-role-of-smart-irrigation-systems/#Precision_Watering_for_Maximum_Efficiency (date of access: 28.10.2025).

Downloads

Published

2026-04-19

How to Cite

Vasylenko , M., & Zahorna , O. (2026). Energy Consumption Monitoring and Anomaly Detection Module for a Smart Automatic Irrigation System. Electronics and Control Systems, 2(88), 118–123. https://doi.org/10.18372/1990-5548.88.20975

Issue

Vol. 2 No. 88 (2026)

Section

ELECTRONICS, ELECTRONIC COMMUNICATIONS, INSTRUMENTATION AND RADIO ENGINEERING

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The scientific journal “Electronics and control systems” adheres to the principles of Open Access and provides free, immediate, and permanent access to all published materials without financial, technical, or legal barriers for readers.

All articles are published in Open Access under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Copyright

Authors who publish their works in the journal “Electronics and control systems”:

  • retain the copyright to their publications;

  • grant the journal the right of first publication of the article;

  • agree to the distribution of their materials under the CC BY 4.0 license;

  • have the right to reuse, archive, and distribute their works (including in institutional and subject repositories), provided that proper reference is made to the original publication in the journal.