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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Ahmed El Oualkadi
Abdelmalek Essaadi University
Computer Science & IT Electrical & Electronics Engineering Engineering

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An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN Aziz Mahboub; El Mokhtar En-Naimi; Mounir Arioua; Hamid Barkouk; Younes El Assari; Ahmed El Oualkadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (839.545 KB) | DOI: 10.11591/ijece.v9i5.pp4192-4203

Abstract

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period.
A new design of 5G multilayers planar antenna with the enhancement of bandwidth and gain Abderrahim Bellekhiri; Noha Chahboun; Jamal Zbitou; Yassin Laaziz; Ahmed El Oualkadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1502-1510

Abstract

In this work, we design a microstrip patch antenna having a dimension of 3.279x4.232 mm2 and consisting of a Foam-like substrate, of a relative dielectric permittivity of 1 and with a width of 0.5 mm, placed between two identical Rogers RT5880 substrates, having a value of 2.2 as relative dielectric permittivity, a loss tangent of 0.0009 and a height of 0.508 mm. The designed antenna resonates at 28 GHz, featuring a maximum gain of 9.77 dBi and a wide frequency bandwidth of 2.9 GHz. Compared to the conventional antenna, this proposed structure achieved an important enhancement of the directivity, with a value around 38.8°. The CST Microwave Studio software was used for all designs and analysis.
YOLOv5: an improved algorithm for real-time detection of industrial defective pieces Abdelaziz Elbaghdadi; Yassine Yazid; Ahmed El Oualkadi; Antonio Guerrero-González; Soufiane Mezroui
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp744-755

Abstract

The rapid advancement of communication technologies and the growing demand for artificial intelligence are transforming traditional manufacturing into smart industries. Robotic arms and smart vision cameras are widely adopted to support industrial internet of things (IIoT) applications. Beyond enhancing production efficiency and quality, these technologies play a crucial role in cost reduction, energy savings, and improving operator safety. In this article, we propose an intelligent industrial system using an improved version of the you only look once (YOLO) algorithm for defect detection on production lines. The system integrates robots and cameras to automate defect inspection and classification of manufactured pieces. An updated YOLOv5 model is designed as an end-to-end solution for detecting surface defects in three specific regions. We trained and evaluated the model using custom data tailored to the inspected pieces. The system achieved a 99% mean average precision (mAP) and an 80% recall rate. Additionally, it delivers a 99% detection rate at high speed, enabling real-time surface defect detection. This method not only accurately predicts defective locations but also provides size information, which is critical for assessing the quality of newly produced pieces.
Co-Authors Abdelaziz Elbaghdadi Abderrahim Bellekhiri Antonio Guerrero-González Aziz Mahboub El Mokhtar En-Naimi Hamid Barkouk Jamal Zbitou Mounir Arioua Noha Chahboun Soufiane Mezroui Yassin Laaziz Yassine Yazid Younes El Assari