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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 65 Documents
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Search results for , issue "Vol 30, No 3: June 2023" : 65 Documents clear
Estimation of coverage and energy in bio inspired wireless sensors using Harris hawk algorithm Hakeem Abdul Wasay; Kavipriya Periyasamy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1813-1820

Abstract

Wireless sensor networks have various sensors which are wide spread and also equipped with supplies. For the deployment sensor nodes are used for capturing the information, the region of interest is selected and the nodes are deployed. Lower sensing power degrades the DC supply reducing the life of wireless sensor networks, this can also be due to improper sensor deployment. Based on the above various wireless sensor network algorithms are available to compute and implement the required optimal figures. Harris hawk is among the one such algorithm used in wireless sensors. It works on the principle of the bird Harris hawk which catches the prey from a very high altitude, resemblance to this and many other features it is implemented in wireless sensors. Various wireless sensor characteristics can be found, figured and tabulated which are essential in this domain. The characteristics like coverage, connectivity, location, energy, and can be estimated. In the work the coverage and energy fitness is estimated using Harris hawk algorithm and its results are being illustrated.
Optimal sliding mode controller for lower limb rehabilitation exoskeleton in constrained environments Mohammad A. Faraj; Boutheina Maalej; Nabil Derbel
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1458-1469

Abstract

In this article, a lower limb exoskeleton (LLE) under contacting constrained motion has been modelled using augmented Lagrange equations which include Lagrange multiplier and Jacobian vectors. A sliding mode Controller optimized by the grey Wolf optimization algorithm has been used for controlling (LLE) in the case of constrained motion with uncertainties and outside perturbation. The grey wolf optimization algorithm has been used as an optimization algorithm for finding the optimal controllers’ parameters in order to improve the performance of the system. The stability analysis of the closed-loop system has been performed using Lyapunov theory of stability. To validate the effectiveness of the proposed controller structure grey wolf optimization algorithm controller (GW-SMC), a series of comparative simulations have been carried out with other types of recently existing sliding mode control (SMC). The results of numerical simulations indicate the superiority of the sliding mode optimized by the GW-SMC over other types of recently existing controller in terms of tracking errors and robustness towards uncertainties and external disturbances.
Assessment of a single-phase single-stage grid-connected photovoltaic system Nurhazwani Anang; Wan Mariam Wan Muda; Muhamad Zalani Daud
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1339-1347

Abstract

A grid-connected photovoltaic (GCPV) system plays an important role in the development of green technology. However, generated photovoltaic (PV) power that is injected into the grid causes instability in the grid system. Previous studies have shown that power quality for a three-phase system is thoroughly being discussed, but not for a single-phase system. Single-phase system also contribute to instability in low-voltage grid networks during high power penetration as majority of the single-phase GCPV nowadays are installed on rooftops. Thus, in this study, the power quality of a single-phase single-stage GCPV system is investigated based on the total harmonic distortion (THD), power factor (PF), and the generated active (P) and reactive (Q) power during different solar irradiance and varying loads conditions. A model of the GCPV system was developed in MATLAB/Simulink, so that certain variables can be varied to observe their effect towards the power quality. The results show that the current and voltage of generated PV power are synchronized and having low current THD which is less than 1% for all cases. PF values are also in the acceptable range in compliance to IEC 61727 standard which is 0.9971, and the generated PQ is in accordance to the connected load.
University of Kufa unified laboratories management system using computer application Faris Sattar Hadi; Ali Al Farawn; Ahmed Hazim Alhilali
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1617-1623

Abstract

The laboratory organization is essential in the university to maximize system convenience, accuracy, appropriateness, and sustainability. The laboratory data system is an information supplier that aids in arranging data sources and decision-making processes. In this work, unified laboratories management system (ULMS) was presented in the educational field for managing and scheduling lab equipment information. There are two steps in the research process: the first is to examine the old approach for organizing and scheduling laboratory equipment and suggest a better one. The approach adopted in this system is the first come, first served rule governs task priority (FCFS). The second step is creating a computerized system for scheduling and managing laboratory equipment. For programming, C# and structured query language (SQL) are used. This system's design included user and administrative integration (manager, technicians, and researchers). An information application system plan was created because of this research to manage the scheduling information for lab equipment. As a result, it can help the management of the laboratory describe all operational tasks in a way that is considerably simpler and produces outcomes more quickly and accurately.
Effective resource virtualization for dynamic IoT devices in road network Padmanabhan P.; Sampath Kumar K.; John A.
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1777-1785

Abstract

Internet of things (IoT), which is considerably innovating and generating a large volume of processes in every field worldwide, is one of the recent and next disruptive technologies. As a result, IoT devices and others are increasing network connections in the relevant field. It is essential to maximize and process these kinds of resources. The effective usage of resources is one of the most important and very difficult to manage the resource in the dynamic environments. Many studies are performed in the effective usage of resource in the static and dynamic environments. However, the dynamic environments have still different issues and have to solve different dynamic networking issues. In this work, present a mechanism for managing different connecting devices in the dynamic environments. Especially this system is concentrating on road network device management in dynamic environments. The proposed system called dynamic road sensing (DyRSen) connectivity is support to different continuous connectivity. The DyRSen provides: i) continuous connectivity using available resources and provide virtual environment for computing, ii) temporary data storage in dynamic environment for effective resource sharing, and iii) reduce the energy utilization and network overhead and the effective resource management is compared to the other works.
Voltage and frequency stabilization by fuzzy integrated droop control of a multi renewable source micro grid Savitri Swathi; Bhaskaruni Suresh Kumar; Jalla Upendar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1308-1320

Abstract

A multi renewable source micro-grid system has many power quality issues when it is operated in grid islanding condition. During grid connected mode the voltage and frequency of the system will remain stable for small disturbances like load changes or environmental changes. During these sudden variations in the system, the grid supports the load maintaining the system stable. In this paper a droop control is introduced for the renewable source module 3-ph inverter during standalone mode supporting the load. For detection of grid islanding, an active islanding detection control is adopted which makes the 3-ph inverter to shift from synchronous reference frame (SRF) control to droop control. The performance of the droop control is improvised with fuzzy interference structure (FIS) module replacing the conventional proportional integral and derivative (PID) control. A comparative analysis is done in this paper with different controllers in droop control scheme using matrix laboratory (MATLAB) Simulink software. Stability analysis is carried out on the system determining the voltage and frequency fluctuations during grid disturbances. There is an improvement in load compensation, voltage ripple, voltage magnitude, frequency ripple and settling time with the introduced fuzzy droop controller.
Harmful gases detection using artificial neural networks of the environment Pratiksha Rai; Syed Hasan Saeed; Shri Om Mishra
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1389-1398

Abstract

This work describes a small, low-cost electronic nose device which can detect harmful substances that can harm human health, such as flammable gas like acetone, ethanol, butane as well as methane, among others. An artificial olfactory instrument consists of a set of metal oxide semiconductor sensors as well as a computer-based communications channel for signal gathering, proceeding, and presentation. We used three sensors instead of six, and the results were plotted as a variance, score as well as loading plot with crossvalidation. For gas identification, we use artificial neural network (ANN) and compare them to parallel factor analysis. Electronic nose (e-nose) has provided numerous benefits in a variety of logical study disciplines. Our goal is to create a sensor exhibit framework that can discriminate the most exceedingly contaminated gases while also being extremely responsive, precise, and less power consuming. Thus, for gas detection, we employ an ANN as well as make a comparison of results with parallel factor analysis (PARAFAC).
Design and fabrication of an IoT-based smart electrical meter for residential energy management Thanh Ba Nguyen; Tri Cao Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1259-1268

Abstract

Transparency in electricity measurement and efficient use of electricity are issues of concern to households. Electricity customers want to have confidence in their utility company's electricity meters installed at their houses. This study designs and constructs an internet of things (IoT)-based smart electric meter to measure electricity and remotely control domestic appliances. This device can monitor, calculate electricity bills and remotely control the appliances via the internet; electrical quantities are displayed in real-time on the Blynk app, liquid crystal display (LCD) screen and Google Sheet. The device is also capable of emailing the electricity user. The proposed system is designed and developed based on ESP32, a LCD, a PZEM 004T, four relays and a DC source. The results show that the device works stably and the device’s error is less than 5%. This research makes it possible for users to conveniently monitor their power consumption while enhancing their energy-saving awareness.
Anomaly-based intrusion detection system based on feature selection and majority voting Mina Eshak Magdy; Ahmed M. Matter; Saleh Hussin; Doaa Hassan; Shaimaa Ahmed Elsaid
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1699-1706

Abstract

Recently, cyberattacks have been more complex than in the past, as a new cyber-attack is initiated almost every day. Therefore, researchers should develop efficient intrusion detection systems (IDS) to detect cyber-attacks. In order to improve the detection and prevention of the aforementioned cyber-attacks, several articles developed IDSs exploiting machine learning and deep learning. In this paper, a way to find network intrusions using a combination of feature selection and adoptive voting is investigated. NSL-KDD dataset, a high-dimensional dataset that has been widely used for network intrusion detection, is applied in this approach. Feature selection plays an important role for improving accuracy and testing time as it eliminates the less significant attributes from the data set, thus saving computational power and effort. The experimental results show that the proposed approach achieves an accuracy of 86.5% on the NSL-KDD test dataset using an adoptive voting algorithm trained with the selected features. In addition, the time to process each record is 97.5 microseconds, which reflects the proposed model's superior performance. Comparing the proposed model with the existing models in the literature shows that the proposed adaptive voting approach significantly improves intrusion detection accuracy, enhances computational efficiency, and reduces false positives.
Utilizing deep neural network for web-based blood glucose level prediction system Ganjar Alfian; Yuris Mulya Saputra; Lukman Subekti; Ananda Dwi Rahmawati; Fransiskus Tatas Dwi Atmaji; Jongtae Rhee
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1829-1837

Abstract

Machine learning algorithms can be used to forecast future blood glucose (BG) levels for diabetes patients, according to recent studies. In this study, dataset from continuous glucose monitoring (CGM) system was used as the sole input for the machine learning models. To forecast blood glucose levels 15, 30, and 45 minutes in the future, we suggested deep neural network (DNN) and tested it on 7 patients with type 1 diabetes (T1D). The suggested prediction model was evaluated against a variety of machine learning models, such as k-nearest neighbor (KNN), support vector regression (SVR), decision tree (DT), adaptive boosting (AdaBoost), random forest (RF), and eXtreme gradient boosting (XGBoost). The experimental findings demonstrated that the proposed DNN model outperformed all other models, with average root mean square errors (RMSEs) of 17.295, 25.940, and 35.146 mg/dL over prediction horizons (PHs) of 15, 30, and 45 minutes, respectively. Additionally, we have included the suggested prediction model in web-based blood glucose level prediction tools. By using this web-based system, patients may readily acquire their future blood glucose levels, allowing for the generation of preventative alarms prior to crucial hypoglycemia or hyperglycemic situations.

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