Development of methods for monitoring and optimization of underground drainage systems using wireless sensor networks and ultra-wideband antennas

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.310360

Keywords:

ultra-wideband, antenna optimization, GPON, energy efficiency, network longevity, neural networks

Abstract

This research focuses on optimizing ultra-wideband (UWB) antennas, which are critical in modern communication systems due to their wide frequency range (3.1–10.6 GHz) and high data transmission capabilities. The study addresses the challenge of optimizing key antenna parameters – such as return loss, peak gain, and radiation efficiency – while also ensuring energy efficiency and network longevity. Traditional optimization methods, such as LEACH-C, often fail to balance these factors, leading to suboptimal performance.

To solve this problem, the researchers developed the Generalized Position-based Optimization Neural Network (GPON) for UWB antenna optimization. They also evaluated the Position-based Hybrid Neural Network (PAN) method, comparing its performance with existing algorithms including LEACH-C, Firefly Algorithm (FA), HFAPSO, FA-ANN, and HWOABCA. The GPON model reduced return loss to 25.5 dB at 3.5 GHz and improved peak gain to 4.2 dB i, while maintaining 92 % radiation efficiency. In contrast, PAN demonstrated a 15–25 % improvement in residual energy and extended network lifetime by 20 % compared to LEACH-C.

These improvements were due to the integration of advanced neural network techniques in GPON and the effective use of positional data in PAN, enabling more precise and adaptive optimization. The ability to balance multiple performance metrics simultaneously – a challenge previous models struggled with – is a key feature. This balance is crucial for UWB antennas in communication systems where both performance and energy efficiency are vital. The findings are especially relevant for practical applications in wireless sensor networks, mobile communications, and radar systems, requiring long-term network reliability and optimal antenna performance

Author Biographies

Kabi Yelikbay, ALT University

Doctoral Student

Department Information and Communication Technologies

Pramod Kumar, CMR Engineering College

Associate Professor, AIML (ECE)

Department of Electronics and Communication Engineering

Ruslan Kassym, ALT University; University of Jaén

Supervisor Project, Researcher

Tansaule Serikov, S.Seifullin Kazakh Agrotechnical Research University

Doctor PhD

Department of Information and Communication Technology

Maxat Orunbekov, ALT University

Senior Lecturer

Department Information and Communication Technologies

Ayinuer Turdy, ALT University

Senior Lecturer

Department Information and Communication Technologies

Marzhan Temirbekova, ALT University

PhD, Associate Professor

Arai Tolegenova, S.Seifullin Kazakh Agrotechnical Research University

PhD, Associate Professor

Department of Information and Communication Technology

Akmaral Tlenshiyeva, ALT University

Senior Lector

Department Information and Communication Technologies

Makbal Kassymova, S.Seifullin Kazakh Agrotechnical Research University

Researcher

Department of Information and Communication Technology

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Development of methods for monitoring and optimization of underground drainage systems using wireless sensor networks and ultra-wideband antennas

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Published

2024-10-31

How to Cite

Yelikbay, K., Kumar, P., Kassym, R., Serikov, T., Orunbekov, M., Turdy, A., Temirbekova, M., Tolegenova, A., Tlenshiyeva, A., & Kassymova, M. (2024). Development of methods for monitoring and optimization of underground drainage systems using wireless sensor networks and ultra-wideband antennas. Eastern-European Journal of Enterprise Technologies, 5(5 (131), 26–36. https://doi.org/10.15587/1729-4061.2024.310360

Issue

Vol. 5 No. 5 (131) (2024): Applied physics

Section

Applied physics

License

Copyright (c) 2024 Kabi Yelikbay, Pramod Kumar, Ruslan Kassym, Tansaule Serikov, Maxat Orunbekov, Ayinuer Tuerdi, Marzhan Temirbekova, Arai Tolegenova, Akmaral Tlenshiyeva, Makbal Kassymova

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