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All Journal JURNAL NASIONAL TEKNIK ELEKTRO Andalas Journal of Electrical and Electronic Engineering Technology
Muguro, Joseph
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Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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A Comprehensive Review of Intelligent Reflecting Surfaces from Hardware to Industrial Integration and Future Directions Munira, Anne; Muguro, Joseph; njeri, waweru
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 4 No. 1 (2024): May 2024
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v4i1.100

Abstract

An Intelligent Reflecting Surface (IRS) has emerged as a key solution to performance bottlenecks in wireless communication. Its ability to combat multipath fading and improve signal and energy efficiencies has made it relevant to various industry applications, including the Internet of Things (IoT), smart manufacturing, cognitive radio, radar, and Multiple-Input Multiple-Output (MIMO) systems. This paper presents a comprehensive review of the IRS’s structure and hardware requirements, channel estimation, optimization methods, and key applications to enable readers to understand how the IRS operates, its benefits, and some of the challenges involved in its application. The structure and hardware requirements are important to understand as they dictate the material composition, number, and arrangement of reflecting elements, and their reconfigurability. Channel State Information (CSI) plays a crucial role in optimized transmission as it gives information on the channel conditions, enabling users to tailor their transmission accordingly. In this work, all scholarly papers related to the IRS published between 2010-2024 were considered, sampled, and categorized based on the key themes. An analysis of the hardware and architecture reveals that transceiver hardware imperfections significantly affect IRS optimization and should be considered. While several channel estimation techniques offer comparable benefits, accuracy turns out to be the most important factor to consider. Further, results show that flexibility and inference accuracy make machine learning techniques superior to other optimization methods. Still, challenges remain in relation to IRS standardization, privacy concerns, and handover techniques that ought to be addressed for future industrial integration.
Enhancing Interface Efficiency: Adaptive Virtual Keyboard Minimizing Keystrokes in Electrooculography-Based Control Anandika, Arrya; Laksono, Pringgo Dwi; Suhaimi, Muhammad Syaiful Amri bin; Muguro, Joseph; Rusydi, Muhammad Ilhamdi
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 3: November 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n3.1160.2023

Abstract

Rapid technological developments, one of which is technology to build communication relationships between humans and machines using Biosignals. One of them is Electrooculography (EOG). EOG is a type of biosignals obtained from eye movement. Research related to EOG has also developed a lot, especially for virtual keyboard control. Research on virtual keyboard control based on eye gaze motion using electrooculography technology has been widely developed. Previous research mostly drew conclusions based on time consumption in typing paragraphs. However, it has not been seen based on the number of eye gaze motions made by the user. In this research, an adaptive virtual keyboard system is built, controlled using EOG signals. The adaptive virtual keyboard is designed with 7x7 dimensions and has 49 buttons, including main buttons, letters, numbers, symbols, and unused buttons. The layout of the adaptive virtual keyboard has six zones. Each zone has a different number of steps. Characters located in the same zone have the same number of steps. The adaptive feature is to rearrange the position of the character's button based on the previously used characters. In the experiments, 30 respondents controlled static and adaptive virtual keyboards with 7 paragraphs typed. Adaptive mode rearranges the position of buttons based on k-selection activities from respondents. the k numbers are 10, 30, 50, 70 and 100. Two virtual keyboard modes are evaluated based on the number of steps required to type the paragraphs. Test results show that the performance of the adaptive virtual keyboard can shorten the number of user steps compared to static mode. There are tests of the optimal system that can be reduced up to 283 number of steps and from respondents, that can reduced up to 258 number of steps or about 40% of steps. This research underscores the promise of EOG-driven adaptive virtual keyboards, signaling a notable stride in augmenting user interaction efficiency in typing experiences, heralding a promising direction for future human-machine interface advancements.
Co-Authors Anandika, Arrya Laksono, Pringgo Dwi Muhammad Rusydi H. Munira, Anne Njeri, Waweru Suhaimi, Muhammad Syaiful Amri Bin