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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 30, No 2: May 2023" : 64 Documents clear
Implementation of a secure wireless communication system using true random number generator for internet of things Huirem Bharat Meitei; Manoj Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp982-992

Abstract

This paper describes the design and implementation of an internet of thing (IoT)-based application that uses a true random number generator (TRNG) with an all digital phase locked loop (ADPLL) for secure wireless communication. Field programmable gate array (FPGA) boards were used on the transmitter and receiver sides and were interfaced with Esp8266 chips to wirelessly send and receive encrypted sensor data. The MQ-2 gas sensor and tracking sensor were connected to the FPGA board on the transmitter side, where data from the sensors was encrypted using the exclusive-OR (XOR) function and the TRNG architecture. The system can be controlled by users through a web browser served by the ThingSpeak cloud. The Artix-7 FPGA device is used to implement the proposed wireless communication system, for which design and synthesis were done using the Xilinx Vivado 2015.2 tool. The proposed system uses a low amount of power and is suitable for a standalone, highly secure TRNG-based IoT application. The National Institute of Standard and Testing (NIST SP 800-22) test showed that ADPLL with finite impulse response (FIR) filter-based TRNGs are better for encrypting IoT devices for secure wireless communication.
An optimization of multiple gateway location selection in long range wide area network networks Chutchai Kaewta; Charuay Savithi; Ekkachai Naenudorn
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1011-1020

Abstract

The adoption of smart agricultural technology in rural areas is still limited in terms of network infrastructure supported. As a result, farmers continue to practice traditional farming that mainly focuses on human labor and requires experience in planning the production of agricultural products in unstable weather conditions, which makes the farmers highly risky. Currently, long range (LoRa) technology is a smart agriculture support tool that will enable the Internet of Things devices to a large number of end nodes distributed over a wide geographical area. They could access cloud computing from a long distance, kilometers, for processing via long range wide area network (LoRaWAN) communication protocol. When choosing a multiple gateway location for LoRaWAN networks, big networks must consider the spatial distribution of clients, radio signal propagation, and the cap on the number of devices served access. In this study, a mathematical model is developed to optimize coverage. The LINGO modeling program, an exact software method, was used to test the model. The findings indicated that the best six gateways at the optimal LoRaWAN gateway location. The gateways can provide signal coverage for all end nodes and can manage the capacity of the LoRaWAN gateway to support the proper number of end nodes.
Machine learning algorithms for privacy preserving in vehicular ad hoc network Shazia Sulthana; Byppanahalli Narayana Reddy Manjunatha Reddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1021-1028

Abstract

Machine learning (ML) will improve the outcomes through the use of methods that categorize the information into the predetermined set. This work is to present an estimation and assessment of machine learning techniques for achieving privacy preservation in vehicular ad hoc networks (VANETs). This method generates two distinct group keys for prime and secondary users. Road side units (RSUs) are deployed to broadcast one group key from the trusted authority (TA) to the primary users, and secondary users are utilized to transmit the other group key. The main aim of this network is developed to avoid vulnerable attacks and to enhance the privacy of this network, Naïve Bayesian classifier (BC), support vector machine (SVM), K-nearest neighbor (KNN), artificial neural networks (ANN), Bayesian network (BN) methods are utilized in correlation with the proposed deep neural networks (DNN) with the black widow optimization (BWO) for protection preserving. These learning characterization procedures are assessed concerning delay, network lifetime, throughput, delivery ratio, and drop and this proposed calculation (DNN-BWO) shows improved results than the current methodologies.
Analysis of SSVEP component acquisition from EEG signals for efficient target identification Kalenahally R. Swetha; Ravikumar G. Krishnegowda; Shashikala S. Venkataramu
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp838-845

Abstract

The application of the brain-computer interface (BCI) is massively helpful and advantageous for disabled people. Moreover, BCI is an arrangement of software and hardware interface that provides a direct interaction between the human brain and computer devices. Therefore, in this article, A steady state visual evoked potential (SSVEP)-based BCI system is presented to identify SSVEP components from multi-channel electroencephalogram (EEG) data by minimizing background noise using an adaptive spatial filtering method. Here, the proposed adaptive spatial filtering-based SSVEP component extraction (ASFSCE) model improves reproducibility among multiple trails and identifies targets efficiently by optimizing the Eigenvalue problem. Along with that, the proposed ASFSCE model minimizes computational complexity from O(G2) to to get high target identification accuracy with faster execution. Performance results are measured using the SSVEP dataset. In this dataset, 11 subjects are used to perform experiments and 256-channel EEG data is taken. The efficiency of the proposed ASFSCE model is measured in terms of mean target detection accuracy and mean information transfer rate (ITR) in bits per minute. The average detection accuracy and ITR are evaluated by considering 23 trials for each subject. The obtained detection accuracy is 93.47% and ITR is 308.23 bpm.
Analysis study of the bee algorithms as a mechanism for solving combinatorial problems Hafedh Ali Shabat; Khamael Raqim Raheem
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1091-1098

Abstract

Combinatorial optimization problems are problems that have a large number of discrete solutions and a cost function for evaluating those solutions in comparison to one another. With the vital need of solving the combinatorial problem, several research efforts have been concentrated on the biological entities behaviors to utilize such behaviors in population-based metaheuristic. This paper presents bee colony algorithms which is one of the sophisticated biological nature life. A brief detail of the nature of bee life has been presented with further classification of its behaviors. Furthermore, an illustration of the algorithms that have been derived from bee colony which are bee colony optimization, and artificial bee colony. Finally, a comparative analysis has been conducted between these algorithms according to the results of the traveling salesman problem solution. Where the bee colony optimization (BCO) rendered the best performance in terms of computing time and results.
Speech scrambling based on multiwavelet and Arnold transformations Zahraa Abdulmuhsin Hasan; Suha Mohammed Hadi; Waleed Ameen Mahmoud Al-Jawher
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp927-935

Abstract

For communication applications where secure speech signal transmissions are a key requirement, speech scrambler is taken into consideration. To prevent someone from listening in on private conversations without their knowledge, it can transform clear speech into a signal that is unintelligible. The proposed speech scrambling system involves using two types of frequency transformation techniques: multiwavelet transform and Arnold transform. The effectiveness of the scrambling algorithm was evaluated with the help of three different measurements: the peak signal to noise ratio (PSNR), the estimated time (ET), and the mean square error (MSE). According to the final findings, the outcome of the scrambled speech signal does not have any residual intelligibility, while the quality of the descrambled speech is extremely satisfactory and has a low MSE level.
Neural network based novel controller for hybrid energy storage system for electric vehicles Sagar Sharma; Shakuntla Boora
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp670-680

Abstract

This manuscript deals with the various control strategies of storage system for an electrical vehicle. High demands in the electrical systems in the field of transportations leads to various challenges and more precise control and regulations techniques. Apart from the conventional grid system now a days the integration of renewable energy systems like solar, wind and fuel cell system leads to more complex system but these system shares the load from conventional generating system. This paper deals with the study and control aspects of the electrical vehicles associated with hybrid energy storage (HES) systems. In general, when systems are integrated with the main grid there are more distortions and ripples in the system. To reduce these distortions various control techniques are used. This paper proposes a neural network-based PI (NNPI) controller for HES system for electric vehicles for better distortion less outputs.
Fingerprint biometric voting machine using internet of things Zakiah Mohd Yusoff; Yusradini Yusnoor; Arni Munira Markom; Siti Aminah Nordin; Nurlaila Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp699-706

Abstract

Free elections are one of democracy's principles. Elections will be used to choose the representatives of the people. It is underlined on how important it is to organize free, fair, and secret elections. Traditionally, voting used to be conducted by stamping on paper, then placing it in a ballot box with the chosen candidate. Each vote in every ballot box must be counted separately, and the votes for each contender must then be added up to determine which candidate had the most votes. Everything was done manually, it will take longer to announce the winner. Numerous errors are being made, but they will not change the outcome. In this study, a significant system that stops electoral malpractices and expedites the voting process will propose. The controller utilized in this project is the Arduino Uno. The user is authenticated using a fingerprint. Everybody's fingerprints differ from one another. The device is programmed using the Arduino IDE, and the ballot card is displayed, and the results are stored in the cloud. Only a registered voter may cast a vote, and the system alerts users to any fraud. This project protects citizens' freedom to vote and ensures an impartial election.
A novel decision-making approach based on a decision tree for micro-grid energy management Ibtissame Mansoury; Dounia El Bourakadi; Ali Yahyaouy; Jaouad Boumhidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1150-1158

Abstract

Environmental challenges such as climate change have accelerated humanity's need for renewable alternative energy sources. For this reason, we propose in this paper a decision-making strategy that allows controlling the flows of energy into a micro-grid (MG) compound of solar energy, batteries, and diesel generator (DG), and connected to the distributed network (DN). Therefore, the power supply to the loads is obtained either from the energy produced by solar sources, from the batteries, from the DN, or from the DG when renewable energy (RE) and batteries are depleted. To make the final decision, we consider four parameters at the same time: the energy produced by solar energy, the requested load, the state of charge of batteries (SoC), and the purchase or sale price. Decision tree (DT) is used to build the energy management strategy to ensure the availability of power on demand by making logical decisions about charging batteries, discharging batteries, buying necessary energy from DN, selling excess energy to DN, and recovering necessary energy from DG. The suggested DT approach is applied to a real MG to minimize the cost-benefit balance, and the comparison analysis demonstrates good results when compared to related works.
The impact of using phase-shift transformers on transmission lines Ayman Y. Al-Rawashdeh; Abdallah R. Alzyoud; Khalaf Y. Alzyoud; Jawdat S. Alkasassbeh; Ashraf Samara
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp651-658

Abstract

Phase shift transformers (PST) are a special type of transformers used to regulate active and reactive power on 3-phase transmission networks by adjusting the difference of voltage phase angle between system nodes. Problems related to power flow and stability, particularly voltage stability issues, are important at the extra high voltage (EHV) and ultra high voltage (UHV) levels due to their extreme sensitivity to active and reactive power changes. Several studies investigated these problems using three-phase systems. Accordingly, this research aims to demonstrate the impact of using PST with single and double transmission lines and to compare its performance under various operational modes.

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